DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant's arguments filed 03/26/2026 have been fully considered but they are not persuasive. Applicant argues on page 19 of Applicant’s Remarks that “Applicant respectfully submits that Wang does not teach nor suggest at least "determining the second lower limb control parameter according to reference positions and reference velocities of a plurality of lower limb joints in the reference data and the barycenter velocity error, wherein the second lower limb control parameter comprises control parameters corresponding to the plurality of lower limb joints," and "tracking a barycenter line momentum and an upper body attitude as the target... wherein determining the first lower limb control parameter of the robot according to the reference data and the actual data with tracking the barycenter line momentum and the upper body attitude as the target comprises: determining a reference barycenter line momentum and a reference barycenter position according to the reference data; determining an actual barycenter line momentum and an actual barycenter position according to the actual data; determining a first external force of a first foot bottom and a second external force of a second foot bottom of the robot according to a barycenter line momentum tracking control law and a tracking control law of the upper body attitude based on the reference barycenter line momentum, the reference barycenter position, the actual barycenter line momentum, and the actual barycenter position; and determining the first lower limb control parameter according to the first external force and the second external force, wherein the first lower limb control parameter comprises the control parameters corresponding to the plurality of lower limb joints," as recited by independent claim 1, as hereby amended.” and “Applicant submits that Doi and Chinese Reference No. CN 115202378 (Wu et al., hereinafter Wu) fail to cure the deficiencies of Wang.”. The Examiner respectfully disagrees. Wang teaches determining the second lower limb control parameter according to reference positions and reference velocities of a plurality of lower limb joints in the reference data (See at least Para [0030], Para [0031], Para [0032], Fig 2- Fig 5 shows a plurality of lower limb joints of the robot are being controlled), however, Wang depends on Doi in the rejection for the teaching of barycenter velocity error (See at least Para [0018]). Therefore, it would have been obvious to one of the ordinary skill in the art to combine the teachings of Doi with Wang to get the result related to barycenter velocity error.
Also, Applicant argues on page 20 of the Applicant’s Remarks that “Consequently, Applicant
submits that the contact force in Doi is clearly distinct from the second lower limb control parameter in the claimed subject matter in terms of the target object and physical meaning, and the contact force cannot be equated with the lower limb control parameter.”. The Examiner respectfully disagrees. Doi teaches control the force contact force acting on each contact point between the hand or foot and the environment (See at least Para [0008], Para [0009], Para [0012], Para [0013]).
Applicant further argues on page 20 and Page 21 of the Applicant’s Remarks that “Applicant notes that the position and speed of the center of gravity in Doi are estimated values calculated by the center-of-gravity estimation device, which do not belong to reference values, and the position and speed in Doi all correspond to the center of gravity. However, the reference data in the claimed subject matter, as hereby amended, are reference physical values corresponding to the plurality of target parts when the robot performs the target motion. In other words, the reference positions and reference velocities in the claimed subject matter are reference physical values corresponding to the plurality
of target parts. Therefore, the position and speed of the center of gravity in Doi are clearly distinct from the reference positions and reference velocities in the claimed subject matter in terms of physical meaning and the corresponding objects, and the position and speed of the center of gravity in Doi cannot be equated with the reference positions and reference velocities in the claimed subject matter.
In addition, Applicant notes that Doi only uses the position and speed of the center of gravity to control the robot. Although Doi discloses that the position and speed of the center of gravity include error, it only describes the generation process of the barycenter velocity error. Doi does not use the barycenter velocity error combined with the reference positions and reference velocities to determine the lower limb control parameter. In other words, Doi does not use the three types of information, namely the reference positions, reference velocities, and barycenter velocity error, to jointly determine the lower limb control parameter.”. The Applicant respectfully disagrees. Wang already teaches reference values corresponding to the plurality of target parts when the robot performs the target motion (See at least Fig 1B, Para [0019], Para [0022], Para [0037]). Wang depends on Doi in the rejection for the teachings of barycenter velocity error (Para [0018]). Therefore, it would have been obvious to one of the ordinary skill in the to combine the teachings of Doi with Wang and include the feature of barycenter velocity error, thereby provide improved stability.
In addition, Applicant argues on page 21 and Page 22 of the Applicant’s Remarks that “Consequently, Applicant submits that Doi does not teach nor suggest at least "determining the second lower limb control parameter according to reference positions and reference velocities of a plurality of lower limb joints in the reference data and the barycenter velocity error, wherein the second lower limb control parameter comprises control parameters corresponding to the plurality of lower limb joints," as recited by independent claim 1, as hereby amended. Furthermore, paragraph [0087] of the specification of the present application provides that, since a forward and backward barycenter velocity is prone to departing from an expected reference barycenter velocity, the present application determines the second lower limb control parameter according to the reference positions and reference velocities of the plurality of lower limb joints and the barycenter velocity error during the flight phase, thereby enabling tracking of the expected barycenter velocity during the flight phase. However, as specified in paragraph [0011] of Doi: (2) The center-of-gravity trajectory generation unit generates a center-of-gravity trajectory of the robot 100 that is stable within a predetermined time with the current state as the initial state based on the planned time- series contact point information. It follows that Doi does not recognize that the barycenter velocity of the robot is prone to departing from the expected reference barycenter velocity during the flight phase. The technical solution of Doi only tracks the center-of-gravity trajectory and does not consider tracking the expected barycenter velocity during the flight phase. Consequently, Applicant submits that, before the effective filing date of the claimed invention, one having ordinary skill in the art would have no motivation to combine the method of Wang with the teachings of Doi to obtain the recited "determining the second lower limb control parameter according to reference positions and reference velocities of a plurality of lower limb joints in the reference data and the barycenter velocity error, wherein the second lower limb control parameter comprises control parameters corresponding to the plurality of lower limb joints.". The Examiner respectfully disagrees. Doi teaches that the barycenter velocity of the robot is prone to departing from the expected reference barycenter velocity during the flight phase (See at least Para [0018] “Furthermore, by integrating the translational acceleration of the center of gravity G including this error, the error may be accumulated and the position and speed of the center of gravity may become an estimated value deviated from the true value…”).
Consequently, Applicant argues on page 22 of the Applicant’s Remarks that “Furthermore, Applicant submits that Doi does not teach nor suggest "tracking a barycenter line momentum and an upper body attitude as the target... wherein determining the first lower limb control parameter of the robot according to the reference data and the actual data with tracking the barycenter line momentum and the upper body attitude as the target comprises: determining a reference barycenter line momentum and a reference barycenter position according to the reference data; determining an actual barycenter line momentum and an actual barycenter position according to the actual data; determining a first external force of a first foot bottom and a second external force of a second foot bottom of the robot according to a barycenter line momentum tracking control law and a tracking control law of the upper body attitude based on the reference barycenter line momentum, the reference barycenter position, the actual barycenter line momentum, and the actual barycenter position; and determining the first lower limb control parameter according to the first external force and the second external force, wherein the first lower limb control parameter comprises the control parameters corresponding to the plurality of lower limb joints," as recited by independent claim 1, as hereby amended.”. The Examiner respectfully disagrees. Doi teaches tracking a barycenter line momentum and an upper body attitude as the target (See at least Para [0020] “Therefore, the center of gravity estimation apparatus according to the first embodiment combines the equation of the moment around the center of gravity with the estimation of the center of gravity based on the translational force acting on the center of gravity G of the robot and observes the angular momentum around the center of gravity…”, Para [0040] “…The differential operation unit 9 is one specific example of the joint angular velocity calculating means, and differential operation is performed on the joint angle θ of each joint output from each encoder 3 and the joint angular velocity of each joint (θ on the upper side θ Calculate (·). The differential operation unit 9 outputs the calculated joint angular velocity of each joint to the angular momentum calculation unit 10.”).
Furthermore, Applicant argues on page 22 and Page 23 of the Applicant’s Remarks that “In addition, Applicant notes that the Office, at pages 35 and 36 of the Office action, directs specific attention to paragraph 7 on page 3 of Wu: "S2.1: Take the attitude angle B, the position p of the center of mass of the robot, the angular momentum Lcom of the center of mass, and the momentum Pcom of the center of mass line of the robot as the state variable x, x=[B, p, Lcom, Pcom]T, and take the control variable u as Supporting leg sole force f and moment T,u=[f, T]T" teaches the aforementioned technical features. Applicant respectfully disagrees. According to paragraphs 7 and 8 on page 3 of Wu, Wu at most discloses taking the barycenter angular momentum Lcom and barycenter linear momentum Pcom as the state variable x, and the supporting leg sole force f as the control variable u, to construct a state space equation. Specifically, the state space equation is: x= Ax + Bu + C. Therefore, Wu only describes the mathematical relationship between the state variable and the control variable, and does not set any control target. Consequently, Applicant submits that Wu does not teach nor suggest "tracking a barycenter line momentum and an upper body attitude as the target," as recited by independent claim 1, as hereby amended.”. The Examiner respectfully disagrees. Wu discussed using the control variable to predict future state based on the control output of each step, thereby setting a control target (See at least Page 3 Para 10 “According to the recursive formula of the linear time-invariant system, the future state is predicted based on the state and the control output of each step”, Page3 Para 11 “Among them, xl represents the state of the lth step in the future, x0 represents the initial state, Adj represents the
j power of Ad, Adl represents the l power of Ad, and ul-1-j represents the control variable of the l-1-jth step in the future.”). Also, Wu does teach or suggest taking the attitude angle and the momentum of the center of mass line of the robot as state variables which is construed as "tracking a barycenter line momentum and an upper body attitude as the target (See at least Page 3 Para 8 “Take the attitude angle θ, the position p of the center of mass of the robot, the angular momentum Lcom of the center of mass, and the momentum Pcom of the center of mass line of the robot as the state variable x, x=[θ,p, Lcom, Pcom]T, and take the control variable u as Supporting leg sole force f and moment τ, u=[f,τ]T”)
In addition, Applicant argues on page 23 and Page 24 of the Applicant’s Remarks that “Wu also does not involve the concepts of reference data and actual data. Therefore, the barycenter angular momentum and barycenter linear momentum in Wu do not have corresponding reference values and actual values. It follows that Wu does not teach nor suggest "determining a reference barycenter line momentum and a reference barycenter position according to the reference data; determining an actual barycenter line momentum and an actual barycenter position according to the actual data," as recited by independent claim 1, as hereby amended. In addition, although Wu mentions taking the supporting leg sole force f and torque r as the control variable u, this control variable u refers to the control variable of the state space equation. According to the state space equation of Wu, changes in the control variable u will cause changes in the state variable x. In other words, the supporting leg sole force f will cause changes in the barycenter angular momentum Lcom and barycenter linear momentum Pcom. Therefore, Wu uses the sole force to solve for the barycenter angular momentum and barycenter linear momentum. However, the claimed subject matter, as hereby amended, uses the barycenter angular momentum and barycenter linear momentum to solve for the sole forces of each foot of the robot. Furthermore, the sole force f in Wu is not associated with the tracking of barycenter linear momentum and upper body attitude, nor with the barycenter linear momentum tracking control law and upper body attitude tracking control law. However, the claimed subject matter, as hereby amended, determines a first external force of a first foot bottom and a second external force of a second foot bottom according to the barycenter linear momentum tracking control law and the upper body attitude tracking control law based on the reference barycenter linear momentum, reference barycenter position, actual barycenter linear momentum, and actual barycenter position. The first external force of the foot bottom and the second external force of the second foot bottom are results solved based on the control target and tracking control laws.”. The Examiner respectfully disagrees. Wang already teaches about reference data and actual data. Wang depends on Wu in the rejection for the teachings of barycenter linear momentum and barycenter position (See at least Page 3 Para 8). Therefore, it would have been obvious to one of the ordinary skill in the art to combine the teachings of Wu with Wang, and include the feature of determining a reference barycenter line momentum and a reference barycenter position according to the reference data; determining an actual barycenter line momentum and an actual barycenter position according to the actual data, thereby provide precise calculation for increased movement stability. Also, the control variable is taken as the sole force (See at least Page 6 Para 12) which is combined with the state variable that includes attitude angle θ, the position p of the center of mass of the robot, the angular momentum Lcom of the center of mass, and the momentum Pcom of the center of mass line of the robot as the state variable x (See at least Page 3 Para 8).
Applicant further argues on page 24 of the Applicant’s Remarks that “Consequently, Wu does not teach nor suggest "determining a first external force of a first foot bottom and a second external force of a second foot bottom of the robot according to a barycenter line momentum tracking control law and a tracking control law of the upper body attitude based on the reference barycenter line momentum, the reference barycenter position, the actual barycenter line momentum, and the actual barycenter position," as recited by independent claim 1, as hereby amended. Applicant notes that the supporting leg sole force f in Wu affects the state variables, namely the attitude angle, barycenter position, barycenter angular momentum, and barycenter linear momentum. The attitude angle is a parameter of the robot's upper body/trunk, and the barycenter position, barycenter angular momentum, and barycenter linear momentum are parameters of the barycenter; these four parameters are not control parameters of the lower limb joints. Consequently, Wu does not teach nor suggest "determining the first lower limb control parameter according to the first external force and the second external force, wherein the first lower limb control parameter comprises the control parameters corresponding to the plurality of lower limb joints," as recited by independent claim 1, as hereby amended.”. The Examiner respectfully disagrees as already discussed above.
Applicant further argues on page 25 of the Applicant’s Remarks that “Because Wu aims to improve the modeling accuracy, while the claimed subject matter aims to reduce the dependence on the accuracy of model information, Wu provides an opposite technical teaching. As such, one having ordinary skill in the art would have no motivation to combine the teachings of Wu with those of Wang to obtain "tracking a barycenter line momentum and an upper body attitude as the target... wherein determining the first lower limb control parameter of the robot according to the reference data and the actual data with tracking the barycenter line momentum and the upper body attitude as the target comprises: determining a reference barycenter line momentum and a reference barycenter position according to the reference data; determining an actual barycenter line momentum and an actual barycenter position according to the actual data; determining a first external force of a first foot bottom and a second external force of a second foot bottom of the robot according to a barycenter line momentum tracking control law and a tracking control law of the upper body attitude based on the reference barycenter line momentum, the reference barycenter position, the actual barycenter line momentum, and the actual barycenter position; and determining the first lower limb control parameter according to the first external force and the second external force, wherein the first lower limb control parameter comprises the control parameters corresponding to the plurality of lower limb joints," as recited by independent claim 1, as hereby amended.”. The Examiner respectfully disagrees. Wu does not only aim to improve modeling accuracy, the “invention not only improves the modeling accuracy, but also ensures the stability of the controller, and the overall control method of the present invention has better generality adaptability and robustness” (See at least Page 4 Para 18).
Moreover, Applicant argues on page 24 and Page 25 of the Applicant’s Remarks that “Accordingly, Applicant submits that none of Wang, Doi, and Wu, whether considered individually or in combination with each other, teach or suggest "determining the second lower limb control parameter according to reference positions and reference velocities of a plurality of lower limb joints in the reference data and the barycenter velocity error, wherein the second lower limb control parameter comprises control parameters corresponding to the plurality of lower limb joints" and "tracking a barycenter momentum and an upper body attitude as the target... wherein determining the first lower limb control parameter of the robot according to the reference data and the actual data with tracking the barycenter line momentum and the upper body attitude as the target comprises: determining a reference barycenter line momentum and a reference barycenter position according to the reference data; determining an actual barycenter line momentum and an actual barycenter position according to the actual data; determining a first external force of a first foot bottom and a second external force of a second foot bottom of the robot according to a barycenter line momentum tracking control law and a tracking control law of the upper body attitude based on the reference barycenter line momentum, the reference barycenter position, the actual barycenter line momentum, and the actual barycenter position; and determining the first lower limb control parameter according to the first external force and the second external force, wherein the first lower limb control parameter comprises the control parameters corresponding to the plurality of lower limb joints," as recited by independent claim 1, as hereby amended.”. The Examiner respectfully disagrees. Wang teaches lower limb control parameter (See at least Fig 2- Fig 5, Para [0030], Para [0031], Para [0032]). Wang depends on Wu in the rejection for the teachings of the barycenter line momentum and the upper body attitude as the target (See at least Page 3 Para 8). Therefore, the combination anticipates the provided claim limitations.
The same reasoning as applied to the independent claims above also apply to their corresponding dependent claims.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1, 9, 17, 21 and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. (US20210221455A1) (Hereinafter Wang) in view of Doi et al. (JP2015208790A, attached translated English copy is used for claim mapping) (Hereinafter Doi) and further in view of Wu et al. (CN115202378A) (Hereinafter Wu).
Regarding Claim 1, Wang teaches a method for controlling a robot performed by an electronic device, the method comprising:
obtaining reference data and actual data of the robot at a current control moment (See at least Fig 1B item Flight: Desired Entry, Actual Entry, Entry():Record data), wherein the reference data comprises reference physical values corresponding to a plurality of target parts when the robot performs a target motion, and the actual data comprises actual physical values corresponding to the plurality of target parts when the robot performs the target motion (See at least Fig 1B item Flight: Desired Entry, Actual Entry, Entry():Record data, Para [0037] “In the above-mentioned legged robot continuous hopping control method, each state (i.e., each of the phases) of the robot is divided into the desired entry stage, the actual entry stage, the during stage, and the exit and state transiting stage, thereby composing the finite state machine…”);
determining an actual attitude of the robot according to the actual data, wherein the actual attitude comprises one of a support phase or a flight phase (See at least Fig 1B item Flight: Desired Entry, Actual Entry, Entry():Record data, Fig 1B shows Actual data is collected during Flight, Para [0067] “where, Rfoot is a posture matrix of the sole of the robot…”);
determining a first target control parameter of the robot based on the reference data and the actual data according to the actual attitude (See at least Para [0032] “The single-legged robot 100 adopts the finite state machine in the above-mentioned legged robot continuous hopping control method. Each state (i.e., the phase) of the single-legged robot 100 is divided into the desired entry stage, the actual entry stage, the during stage, and the exit and state transiting stage. During the hop of the single-legged robot 100, the state information of the single-legged robot 100 can be updated in real time. The required state information is output to the planning and control unit so as to generate motion control instructions for the actuators…”, Para [0067] “where, Rfoot is a posture matrix of the sole of the robot…”), wherein the first target control parameter comprises a first lower limb control parameter and a second lower limb control parameter (See at least Fig 2- Fig 5 shows a lower limb joint of the robot are being controlled, Para [0030], Para [0031], Para [0032] “The single-legged robot 100 adopts the finite state machine in the above-mentioned legged robot continuous hopping control method. Each state (i.e., the phase) of the single-legged robot 100 is divided into the desired entry stage, the actual entry stage, the during stage, and the exit and state transiting stage. During the hop of the single-legged robot 100, the state information of the single-legged robot 100 can be updated in real time. The required state information is output to the planning and control unit so as to generate motion control instructions for the actuators. Consequently, the robot is able to hop in different patterns (e.g., height and trajectory) upon given the required state information. FIG. 3 is a schematic diagram of the processes of the continuous hops of different heights performed by the single-legged robot in the embodiment of FIG. 2. As shown in FIG. 3, at the hopping process of sub-diagrams 6 - 10, the robot realizes the continuous hop of different height from the hopping process of sub-diagrams 1 - 5 .”); and
controlling the robot according to the first target control parameter (See at least Para [0032] “The single-legged robot 100 adopts the finite state machine in the above-mentioned legged robot continuous hopping control method. Each state (i.e., the phase) of the single-legged robot 100 is divided into the desired entry stage, the actual entry stage, the during stage, and the exit and state transiting stage. During the hop of the single-legged robot 100 , the state information of the single-legged robot 100 can be updated in real time. The required state information is output to the planning and control unit so as to generate motion control instructions for the actuators. Consequently, the robot is able to hop in different patterns (e.g., height and trajectory) upon given the required state information. FIG. 3 is a schematic diagram of the processes of the continuous hops of different heights performed by the single-legged robot in the embodiment of FIG. 2. As shown in FIG. 3, at the hopping process of sub-diagrams 6 - 10 , the robot realizes the continuous hop of different height from the hopping process of sub-diagrams 1 - 5 .”),
wherein
determining the first target control parameter of the robot based on reference data and the actual data according to the actual attitude comprises:
determining the second lower limb control parameter of the robot according to the reference data and the actual data … in a case that the actual attitude is the flight phase (See at least Fig 1B item Flight: Desired Entry, Actual Entry, Entry():Record data, Fig 1B shows Actual data is collected during Flight, Para [0067] “where, Rfoot is a posture matrix of the sole of the robot…”, Para [0047] “In which, in the during stage of the acceleration phase, the robot will keep performing ground-leaving detections. When changing from the acceleration phase to the flight phase, due to the tracking error of the motion of the robot … The robot first enters from the acceleration phase to the flight phase according to the centroid acceleration planning trajectory. According to the centroid acceleration planning trajectory, the planned transiting time of the robot to change from the acceleration phase to the flight phase can be obtained, so as to determine whether the planned transiting time has come.”, Para [0049] “In which, when the robot has actually entered the flight phase, the theoretical value of the vertical force between the sole of the robot and the ground is zero. In actual applications, the force F.sub.z between sole and ground rapidly reduced to around zero, and a threshold can be used for determining whether the robot gets into the flight phase…”), and
determining the first lower limb control parameter of the robot according to the
reference data and the actual data … in a case that the actual attitude is the support phase (See at least Para [0032] “The single-legged robot 100 adopts the finite state machine in the above-mentioned legged robot continuous hopping control method. Each state (i.e., the phase) of the single-legged robot 100 is divided into the desired entry stage, the actual entry stage, the during stage, and the exit and state transiting stage. During the hop of the single-legged robot 100, the state information of the single-legged robot 100 can be updated in real time. The required state information is output to the planning and control unit so as to generate motion control instructions for the actuators…”, Para [0024] “When it transits between the four stages of each phase and between the adjacent phases, the corresponding states of the robot are different. In which, the transition is driven by the trigger of an event such as the force upon a sole of the robot being greater than a threshold in the flight phase. If the force is greater than the threshold, it means that the robot is landed, and it enters the exit and state transiting stage of the flight phase in the current control cycle and enters the deceleration phase in the next cycle.”, Para [0067] “where, Rfoot is a posture matrix of the sole of the robot…”)…
controlling the plurality of lower limb joints of the robot according to the first lower limb control parameter or the second lower limb control parameter (See at least Fig 2- Fig 5 shows a plurality of lower limb joints of the robot are being controlled, Para [0030], Para [0031], Para [0032] “The single-legged robot 100 adopts the finite state machine in the above-mentioned legged robot continuous hopping control method. Each state (i.e., the phase) of the single-legged robot 100 is divided into the desired entry stage, the actual entry stage, the during stage, and the exit and state transiting stage. During the hop of the single-legged robot 100, the state information of the single-legged robot 100 can be updated in real time. The required state information is output to the planning and control unit so as to generate motion control instructions for the actuators. Consequently, the robot is able to hop in different patterns (e.g., height and trajectory) upon given the required state information. FIG. 3 is a schematic diagram of the processes of the continuous hops of different heights performed by the single-legged robot in the embodiment of FIG. 2. As shown in FIG. 3, at the hopping process of sub-diagrams 6 - 10 , the robot realizes the continuous hop of different height from the hopping process of sub-diagrams 1 - 5 .”, Para [0029] “… In the first control cycle, the desired entry stage and the actual entry stage in the acceleration phase coincide with each other, and a timer starts timing. After the second control cycle, it enters the during phase in the acceleration phase, and detects an event triggered in the acceleration phase. In which, the event in the acceleration phase is defined as that the robot has reached a start-hopping height. If the event is triggered (i.e., the robot is determined to have reached the start-hopping height), it enters the exit and state transiting stage in the current control cycle and enters the desired entry stage of the flight phase in the next control cycle; otherwise, it retains in the during stage of the acceleration phase and the timer is increased by 1 time unit of the control cycle. After it enters the flight phase, the first control cycle is in the desired entry stage, and it enters the during stage after the second control cycle…”) …
Although Wang teaches when changing from the acceleration phase to the flight phase, due to the tracking error of the motion of the robot, the robot has a planned ground-leaving time and an actual ground-leaving time, and the two times are often different, where the actual ground-leaving time of the robot is usually the later (See at least Para [0047]), however, he does not explicitly spell out …
with tracking foot-down points of feet ends as a target … with tracking a barycenter line momentum and an upper body attitude as the target …
wherein determining the second lower limb control parameter of the robot according to
the reference data and the actual data with tracking the foot-down points of the feet ends as the target comprises:
determining a barycenter velocity error of the robot in a target
direction according to the reference data and the actual data, wherein the barycenter velocity error is used for adjusting positions of the foot-down points relative to a barycenter; and
determining the second lower limb control parameter according to reference positions
and reference velocities of a plurality of lower limb joints in the reference data and the barycenter velocity error, wherein the second lower limb control parameter comprises control parameters corresponding to the plurality of lower limb joints;
wherein determining the first lower limb control parameter of the robot according to the reference data and the actual data with tracking the barycenter line momentum and the upper body attitude as the target comprises:
determining a reference barycenter line momentum and a reference barycenter
position according to the reference data
determining an actual barycenter line momentum and an actual barycenter position
according to the actual data
determining a first external force of a first foot bottom and a second external force of a
second foot bottom of the robot according to a barycenter line momentum tracking control law and a tracking control law of the upper body attitude based on the reference barycenter line momentum, the reference barycenter position, the actual barycenter line momentum and the actual barycenter position; and
determining the first lower limb control parameter according to the first external force
and the second external force, wherein the first lower limb control parameter comprising the control parameters corresponding to the plurality of lower limb joints.
Doi teaches …
with tracking foot-down points of feet ends as a target (See at least Para [0028] “… For example, it is assumed that the robot 100 moves with a hand or foot in contact with a predetermined environmental position, and the memory stores the posture and position of each contact point at that time.”)…
determining the second lower limb control parameter of the robot according to the
reference data and the actual data with tracking the foot-down points of the feet ends as the target comprises:
determining a barycenter velocity error of the robot in a target direction according to
the reference data and the actual data, wherein the barycenter velocity error is used for adjusting positions of the foot-down points relative to a barycenter (See at least Para [0018] “…Furthermore, by integrating the translational acceleration of the center of gravity G including this error, the error may be accumulated and the position and speed of the center of gravity may become an estimated value deviated from the true value.”); and
determining the second lower limb control parameter according to reference positions
and reference velocities of a plurality of lower limb joints in the reference data and the barycenter velocity error, wherein the second lower limb control parameter comprises control parameters corresponding to the plurality of lower limb joints (See at least Para [0008] “… The center-of-gravity estimation device is mounted on, for example, a robot. The robot can accurately control the contact force acting on each contact point between the hand or foot and the environment based on the position of gravity and the speed of the robot estimated by the gravity center estimation device.”, Para [0010] “(1) Contact Point Planning When performing a series of tasks set, the trajectory generation unit calculates the position and orientation (time-series contact point information) of the contact point between the environment and the hand or foot of the robot…”, Para [0018] “…Furthermore, by integrating the translational acceleration of the center of gravity G including this error, the error may be accumulated and the position and speed of the center of gravity may become an estimated value deviated from the true value.”);
Therefore, it would have been obvious to one of the ordinary skill in the art before the
effective filing date of the claimed invention to combine the method of Wang with the teachings of Doi and include the feature of tracking foot-down points of feet ends, determining a barycenter velocity error of the robot in a target direction according to the reference data and the actual data, wherein the barycenter velocity error is used for adjusting positions of the foot-down points relative to a barycenter and determining the second lower limb control parameter according to reference positions and reference velocities of a plurality of lower limb joints in the reference data and the barycenter velocity error, wherein the second lower limb control parameter comprises control parameters corresponding to the plurality of lower limb joints, thereby provide improved stability (See at least Para [0011] “(2) Center of Gravity Trajectory Generation The trajectory generation unit generates a center of gravity trajectory of the robot 100 that can maintain its stability until a predetermined time has elapsed with the current state as an initial state, based on the planned time-series contact point information…”).
Wu teaches … with tracking a barycenter line momentum and an upper body attitude as the target (Page 3 Para 7 “S2.1: Take the attitude angle θ, the position p of the center of mass of the robot, the angular momentum Lcom of the center of mass, and the momentum Pcom of the center of mass line of the robot as the state variable x, x=[θ, p, Lcom, Pcom]T, and take the control variable u as Supporting leg sole force f and moment τ, u=[f,τ]T”)…
wherein determining the first lower limb control parameter of the robot according to the reference data and the actual data with tracking the barycenter line momentum and the upper body attitude as the target comprises:
determining a reference barycenter line momentum and a reference barycenter position according to the reference data (See at least Page 3 Para 7 “S2.1: Take the attitude angle θ, the position p of the center of mass of the robot, the angular momentum Lcom of the center of mass, and the momentum Pcom of the center of mass line of the robot as the state variable x, x=[θ, p, Lcom, Pcom]T, and take the control variable u as Supporting leg sole force f and moment τ, u=[f,τ]T”);
determining an actual barycenter line momentum and an actual barycenter position according to the actual data (See at least Page 3 Para 7 “S2.1: Take the attitude angle θ, the position p of the center of mass of the robot, the angular momentum Lcom of the center of mass, and the momentum Pcom of the center of mass line of the robot as the state variable x, x=[θ, p, Lcom, Pcom]T, and take the control variable u as Supporting leg sole force f and moment τ, u=[f,τ]T”);
determining a first external force of a first foot bottom and a second external force of a second foot bottom of the robot according to a barycenter line momentum tracking control law and a tracking control law of the upper body attitude based on the reference barycenter line momentum, the reference barycenter position, the actual barycenter line momentum and the actual barycenter position (See at least Page 3 Para 7 “S2.1: Take the attitude angle θ, the position p of the center of mass of the robot, the angular momentum Lcom of the center of mass, and the momentum Pcom of the center of mass line of the robot as the state variable x, x=[θ, p, Lcom, Pcom]T, and take the control variable u as Supporting leg sole force f and moment τ, u=[f,τ]T”); and
determining the first lower limb control parameter according to the first external force and the second external force, wherein the first lower limb control parameter comprises the control parameters corresponding to the plurality of lower limb joints (See at least Page 3 Para 7 “S2.1: Take the attitude angle θ, the position p of the center of mass of the robot, the angular momentum Lcom of the center of mass, and the momentum Pcom of the center of mass line of the robot as the state variable x, x=[θ, p, Lcom, Pcom]T, and take the control variable u as Supporting leg sole force f and moment τ of the supporting leg sole force f and moment τ, u=[f,τ]T”).
Therefore, it would have been obvious to one of ordinary skill, in the art before the effective filing date of the claimed invention to combine the method of Wang with the teachings of Wu and include the feature of determining the first lower limb control parameter according to the first external force and the second external force, the first lower limb control parameter including control parameters corresponding to a plurality of lower limb joints using a tracking control law of the upper body attitude based on the reference barycenter line momentum, the reference barycenter position, the actual barycenter line momentum and the actual barycenter position, thereby improve the stability of the robot when walking (See at least Page 4 Para 18 “The beneficial effects of the present invention are: compared with the humanoid model predictive control scheme in the prior art, the present invention not only improves the modeling accuracy, but also ensures the stability of the controller, and the overall control method of the present invention has better generality adaptability and robustness.”).
Regarding Claim 9, Wang teaches an electronic device, comprising:
a processor (See at least Para [0023] “FIG. 2 is a schematic block diagram of a robot according to one embodiment. The robot 80 is a biped humanoid robot. In other embodiments, the robot 80 may be a quadruped robot. The robot 80 includes a processor 803, a storage 801, one or more computer programs 802 stored in the storage 801 and executable by the processor 803…”); and
a memory configured to store an instruction executable by the processor (See at least Para [0023] “FIG. 2 is a schematic block diagram of a robot according to one embodiment. The robot 80 is a biped humanoid robot. In other embodiments, the robot 80 may be a quadruped robot. The robot 80 includes a processor 803, a storage 801, one or more computer programs 802 stored in the storage 801 and executable by the processor 803…”);
wherein the processor is configured to:
obtain reference data and actual data of a robot at a current control moment (See at least Fig 1B item Flight: Desired Entry, Actual Entry, Entry():Record data), wherein the reference data comprises reference physical values corresponding to a plurality of target parts when the robot performs a target motion, and the actual data comprises actual physical values corresponding to the plurality of target parts when the robot performs the target motion (See at least Fig 1B item Flight: Desired Entry, Actual Entry, Entry():Record data, Para [0037] “In the above-mentioned legged robot continuous hopping control method, each state (i.e., each of the phases) of the robot is divided into the desired entry stage, the actual entry stage, the during stage, and the exit and state transiting stage, thereby composing the finite state machine…”);
determine an actual attitude of the robot according to the actual data, wherein the actual attitude comprises one of a support phase or a flight phase (See at least Fig 1B item Flight: Desired Entry, Actual Entry, Entry():Record data, Fig 1B shows Actual data is collected during Flight, Para [0067] “where, Rfoot is a posture matrix of the sole of the robot…”);
determining a first target control parameter of the robot based on the reference data and the actual data according to the actual attitude (See at least Para [0032] “The single-legged robot 100 adopts the finite state machine in the above-mentioned legged robot continuous hopping control method. Each state (i.e., the phase) of the single-legged robot 100 is divided into the desired entry stage, the actual entry stage, the during stage, and the exit and state transiting stage. During the hop of the single-legged robot 100, the state information of the single-legged robot 100 can be updated in real time. The required state information is output to the planning and control unit so as to generate motion control instructions for the actuators…”, Para [0067] “where, Rfoot is a posture matrix of the sole of the robot…”), wherein the first target control parameter comprises a first lower limb control parameter and a second lower limb control parameter (See at least Fig 2- Fig 5 shows a lower limb joint of the robot are being controlled, Para [0030], Para [0031], Para [0032] “The single-legged robot 100 adopts the finite state machine in the above-mentioned legged robot continuous hopping control method. Each state (i.e., the phase) of the single-legged robot 100 is divided into the desired entry stage, the actual entry stage, the during stage, and the exit and state transiting stage. During the hop of the single-legged robot 100, the state information of the single-legged robot 100 can be updated in real time. The required state information is output to the planning and control unit so as to generate motion control instructions for the actuators. Consequently, the robot is able to hop in different patterns (e.g., height and trajectory) upon given the required state information. FIG. 3 is a schematic diagram of the processes of the continuous hops of different heights performed by the single-legged robot in the embodiment of FIG. 2. As shown in FIG. 3, at the hopping process of sub-diagrams 6 - 10, the robot realizes the continuous hop of different height from the hopping process of sub-diagrams 1 - 5 .”); and
control the robot according to the first target control parameter (See at least Para [0032] “The single-legged robot 100 adopts the finite state machine in the above-mentioned legged robot continuous hopping control method. Each state (i.e., the phase) of the single-legged robot 100 is divided into the desired entry stage, the actual entry stage, the during stage, and the exit and state transiting stage. During the hop of the single-legged robot 100 , the state information of the single-legged robot 100 can be updated in real time. The required state information is output to the planning and control unit so as to generate motion control instructions for the actuators. Consequently, the robot is able to hop in different patterns (e.g., height and trajectory) upon given the required state information. FIG. 3 is a schematic diagram of the processes of the continuous hops of different heights performed by the single-legged robot in the embodiment of FIG. 2. As shown in FIG. 3, at the hopping process of sub-diagrams 6 - 10 , the robot realizes the continuous hop of different height from the hopping process of sub-diagrams 1 - 5 .”), wherein the processor is further configured to:
determine the second lower limb control parameter of the robot according to the reference data and the actual data … in a case that the actual attitude is the flight phase (See at least Fig 1B item Flight: Desired Entry, Actual Entry, Entry():Record data, Fig 1B shows Actual data is collected during Flight, Para [0067] “where, Rfoot is a posture matrix of the sole of the robot…”, Para [0047] “In which, in the during stage of the acceleration phase, the robot will keep performing ground-leaving detections. When changing from the acceleration phase to the flight phase, due to the tracking error of the motion of the robot … The robot first enters from the acceleration phase to the flight phase according to the centroid acceleration planning trajectory. According to the centroid acceleration planning trajectory, the planned transiting time of the robot to change from the acceleration phase to the flight phase can be obtained, so as to determine whether the planned transiting time has come.”, Para [0049] “In which, when the robot has actually entered the flight phase, the theoretical value of the vertical force between the sole of the robot and the ground is zero. In actual applications, the force F.sub.z between sole and ground rapidly reduced to around zero, and a threshold can be used for determining whether the robot gets into the flight phase…”), and
wherein the processor is further configured to:
control the plurality of lower limb joints of the robot according to the first lower limb control parameter or the second lower limb control parameter (See at least Fig 2- Fig 5 shows a plurality of lower limb joints of the robot are being controlled, Para [0030], Para [0031], Para [0032] “The single-legged robot 100 adopts the finite state machine in the above-mentioned legged robot continuous hopping control method. Each state (i.e., the phase) of the single-legged robot 100 is divided into the desired entry stage, the actual entry stage, the during stage, and the exit and state transiting stage. During the hop of the single-legged robot 100 , the state information of the single-legged robot 100 can be updated in real time. The required state information is output to the planning and control unit so as to generate motion control instructions for the actuators. Consequently, the robot is able to hop in different patterns (e.g., height and trajectory) upon given the required state information. FIG. 3 is a schematic diagram of the processes of the continuous hops of different heights performed by the single-legged robot in the embodiment of FIG. 2. As shown in FIG. 3, at the hopping process of sub-diagrams 6 - 10 , the robot realizes the continuous hop of different height from the hopping process of sub-diagrams 1 - 5 .”, Para [0029] “… In the first control cycle, the desired entry stage and the actual entry stage in the acceleration phase coincide with each other, and a timer starts timing. After the second control cycle, it enters the during phase in the acceleration phase, and detects an event triggered in the acceleration phase. In which, the event in the acceleration phase is defined as that the robot has reached a start-hopping height. If the event is triggered (i.e., the robot is determined to have reached the start-hopping height), it enters the exit and state transiting stage in the current control cycle and enters the desired entry stage of the flight phase in the next control cycle; otherwise, it retains in the during stage of the acceleration phase and the timer is increased by 1 time unit of the control cycle. After it enters the flight phase, the first control cycle is in the desired entry stage, and it enters the during stage after the second control cycle…”) …
Although Wang teaches when changing from the acceleration phase to the flight phase, due to the tracking error of the motion of the robot, the robot has a planned ground-leaving time and an actual ground-leaving time, and the two times are often different, where the actual ground-leaving time of the robot is usually the later (See at least Para [0047]), however, he does not explicitly spell out …
with tracking foot-down points of feet ends as a target … with tracking a barycenter line momentum and an upper body attitude as the target …
the processor is further configured to:
wherein determine a barycenter velocity error of the robot in a target
direction according to the reference data and the actual data, wherein the barycenter velocity error is used for adjusting positions of the foot-down points relative to a barycenter; and
determine the second lower limb control parameter according to reference positions
and reference velocities of a plurality of lower limb joints in the reference data and the barycenter velocity error, wherein the second lower limb control parameter comprises control parameters corresponding to the plurality of lower limb joints;
wherein the processor is further configured to:
determine a reference barycenter line momentum and a reference barycenter
position according to the reference data
determine an actual barycenter line momentum and an actual barycenter position
according to the actual data
determine a first external force of a first foot bottom and a second external force of a
second foot bottom of the robot according to a barycenter line momentum tracking control law and a tracking control law of the upper body attitude based on the reference barycenter line momentum, the reference barycenter position, the actual barycenter line momentum and the actual barycenter position; and
determine the first lower limb control parameter according to the first external force
and the second external force, wherein the first lower limb control parameter comprising the control parameters corresponding to the plurality of lower limb joints.
Doi teaches …
with tracking foot-down points of feet ends as a target (See at least Para [0028] “… For example, it is assumed that the robot 100 moves with a hand or foot in contact with a predetermined environmental position, and the memory stores the posture and position of each contact point at that time.”)…
the processor is further configured to:
determine a barycenter velocity error of the robot in a target direction according to
the reference data and the actual data, wherein the barycenter velocity error is used for adjusting positions of the foot-down points relative to a barycenter (See at least Para [0018] “…Furthermore, by integrating the translational acceleration of the center of gravity G including this error, the error may be accumulated and the position and speed of the center of gravity may become an estimated value deviated from the true value.”); and
determine the second lower limb control parameter according to reference positions
and reference velocities of a plurality of lower limb joints in the reference data and the barycenter velocity error, wherein the second lower limb control parameter comprises control parameters corresponding to the plurality of lower limb joints (See at least Para [0008] “… The center-of-gravity estimation device is mounted on, for example, a robot. The robot can accurately control the contact force acting on each contact point between the hand or foot and the environment based on the position of gravity and the speed of the robot estimated by the gravity center estimation device.”, Para [0010] “(1) Contact Point Planning When performing a series of tasks set, the trajectory generation unit calculates the position and orientation (time-series contact point information) of the contact point between the environment and the hand or foot of the robot…”, Para [0018] “…Furthermore, by integrating the translational acceleration of the center of gravity G including this error, the error may be accumulated and the position and speed of the center of gravity may become an estimated value deviated from the true value.”);
Therefore, it would have been obvious to one of the ordinary skill in the art before the
effective filing date of the claimed invention to combine the method of Wang with the teachings of Doi and include the feature of tracking foot-down points of feet ends, determining a barycenter velocity error of the robot in a target direction according to the reference data and the actual data, wherein the barycenter velocity error is used for adjusting positions of the foot-down points relative to a barycenter and determining the second lower limb control parameter according to reference positions and reference velocities of a plurality of lower limb joints in the reference data and the barycenter velocity error, wherein the second lower limb control parameter comprises control parameters corresponding to the plurality of lower limb joints, thereby provide improved stability (See at least Para [0011] “(2) Center of Gravity Trajectory Generation The trajectory generation unit generates a center of gravity trajectory of the robot 100 that can maintain its stability until a predetermined time has elapsed with the current state as an initial state, based on the planned time-series contact point information…”).
Wu teaches … with tracking a barycenter line momentum and an upper body attitude as the target (Page 3 Para 7 “S2.1: Take the attitude angle θ, the position p of the center of mass of the robot, the angular momentum Lcom of the center of mass, and the momentum Pcom of the center of mass line of the robot as the state variable x, x=[θ, p, Lcom, Pcom]T, and take the control variable u as Supporting leg sole force f and moment τ, u=[f,τ]T”)…
wherein the processor is further configured to:
determine a reference barycenter line momentum and a reference barycenter position according to the reference data (See at least Page 3 Para 7 “S2.1: Take the attitude angle θ, the position p of the center of mass of the robot, the angular momentum Lcom of the center of mass, and the momentum Pcom of the center of mass line of the robot as the state variable x, x=[θ, p, Lcom, Pcom]T, and take the control variable u as Supporting leg sole force f and moment τ, u=[f,τ]T”);
determine an actual barycenter line momentum and an actual barycenter position according to the actual data (See at least Page 3 Para 7 “S2.1: Take the attitude angle θ, the position p of the center of mass of the robot, the angular momentum Lcom of the center of mass, and the momentum Pcom of the center of mass line of the robot as the state variable x, x=[θ, p, Lcom, Pcom]T, and take the control variable u as Supporting leg sole force f and moment τ, u=[f,τ]T”);
determine a first external force of a first foot bottom and a second external force of a second foot bottom of the robot according to a barycenter line momentum tracking control law and a tracking control law of the upper body attitude based on the reference barycenter line momentum, the reference barycenter position, the actual barycenter line momentum and the actual barycenter position (See at least Page 3 Para 7 “S2.1: Take the attitude angle θ, the position p of the center of mass of the robot, the angular momentum Lcom of the center of mass, and the momentum Pcom of the center of mass line of the robot as the state variable x, x=[θ, p, Lcom, Pcom]T, and take the control variable u as Supporting leg sole force f and moment τ, u=[f,τ]T”); and
determine the first lower limb control parameter according to the first external force and the second external force, wherein the first lower limb control parameter comprises the control parameters corresponding to the plurality of lower limb joints (See at least Page 3 Para 7 “S2.1: Take the attitude angle θ, the position p of the center of mass of the robot, the angular momentum Lcom of the center of mass, and the momentum Pcom of the center of mass line of the robot as the state variable x, x=[θ, p, Lcom, Pcom]T, and take the control variable u as Supporting leg sole force f and moment τ of the supporting leg sole force f and moment τ, u=[f,τ]T”).
Therefore, it would have been obvious to one of ordinary skill, in the art before the effective filing date of the claimed invention to combine the method of Wang with the teachings of Wu and include the feature of determining the first lower limb control parameter according to the first external force and the second external force, the first lower limb control parameter including control parameters corresponding to a plurality of lower limb joints using a tracking control law of the upper body attitude based on the reference barycenter line momentum, the reference barycenter position, the actual barycenter line momentum and the actual barycenter position, thereby improve the stability of the robot when walking (See at least Page 4 Para 18 “The beneficial effects of the present invention are: compared with the humanoid model predictive control scheme in the prior art, the present invention not only improves the modeling accuracy, but also ensures the stability of the controller, and the overall control method of the present invention has better generality adaptability and robustness.”).
Regarding Claim 17, Wang teaches a non-transitory computer-readable storage medium, storing a computer program instruction (See at least Para [0076] “When the integrated module/unit is implemented in the form of a software functional unit and is sold or used as an independent product, the integrated module/unit may be stored in a non-transitory computer-readable storage medium. Based on this understanding, all or part of the processes in the method for implementing the above-mentioned embodiments of the present disclosure may also be implemented by instructing relevant hardware through a computer program. The computer program may be stored in a non-transitory computer-readable storage medium, which may implement the steps of each of the above-mentioned method embodiments when executed by a processor…”), wherein the computer program instruction is configured to, when executed by a processor:
obtain reference data and actual data of a robot at a current control moment (See at least Fig 1B item Flight: Desired Entry, Actual Entry, Entry():Record data), wherein the reference data comprises reference physical values corresponding to a plurality of target parts when the robot performs a target motion, and the actual data comprises actual physical values corresponding to the plurality of target parts when the robot performs the target motion (See at least Fig 1B item Flight: Desired Entry, Actual Entry, Entry():Record data, Para [0037] “In the above-mentioned legged robot continuous hopping control method, each state (i.e., each of the phases) of the robot is divided into the desired entry stage, the actual entry stage, the during stage, and the exit and state transiting stage, thereby composing the finite state machine…”);
determine an actual attitude of the robot according to the actual data, wherein the actual attitude comprises one of a support phase or a flight phase (See at least Fig 1B item Flight: Desired Entry, Actual Entry, Entry():Record data, Fig 1B shows Actual data is collected during Flight, Para [0067] “where, Rfoot is a posture matrix of the sole of the robot…”);
determining a first target control parameter of the robot based on the reference data and the actual data according to the actual attitude (See at least Para [0032] “The single-legged robot 100 adopts the finite state machine in the above-mentioned legged robot continuous hopping control method. Each state (i.e., the phase) of the single-legged robot 100 is divided into the desired entry stage, the actual entry stage, the during stage, and the exit and state transiting stage. During the hop of the single-legged robot 100, the state information of the single-legged robot 100 can be updated in real time. The required state information is output to the planning and control unit so as to generate motion control instructions for the actuators…”, Para [0067] “where, Rfoot is a posture matrix of the sole of the robot…”), wherein the first target control parameter comprises a first lower limb control parameter and a second lower limb control parameter (See at least Fig 2- Fig 5 shows a lower limb joint of the robot are being controlled, Para [0030], Para [0031], Para [0032] “The single-legged robot 100 adopts the finite state machine in the above-mentioned legged robot continuous hopping control method. Each state (i.e., the phase) of the single-legged robot 100 is divided into the desired entry stage, the actual entry stage, the during stage, and the exit and state transiting stage. During the hop of the single-legged robot 100, the state information of the single-legged robot 100 can be updated in real time. The required state information is output to the planning and control unit so as to generate motion control instructions for the actuators. Consequently, the robot is able to hop in different patterns (e.g., height and trajectory) upon given the required state information. FIG. 3 is a schematic diagram of the processes of the continuous hops of different heights performed by the single-legged robot in the embodiment of FIG. 2. As shown in FIG. 3, at the hopping process of sub-diagrams 6 - 10, the robot realizes the continuous hop of different height from the hopping process of sub-diagrams 1 - 5 .”); and
control the robot according to the first target control parameter (See at least Para [0032] “The single-legged robot 100 adopts the finite state machine in the above-mentioned legged robot continuous hopping control method. Each state (i.e., the phase) of the single-legged robot 100 is divided into the desired entry stage, the actual entry stage, the during stage, and the exit and state transiting stage. During the hop of the single-legged robot 100 , the state information of the single-legged robot 100 can be updated in real time. The required state information is output to the planning and control unit so as to generate motion control instructions for the actuators. Consequently, the robot is able to hop in different patterns (e.g., height and trajectory) upon given the required state information. FIG. 3 is a schematic diagram of the processes of the continuous hops of different heights performed by the single-legged robot in the embodiment of FIG. 2. As shown in FIG. 3, at the hopping process of sub-diagrams 6 - 10 , the robot realizes the continuous hop of different height from the hopping process of sub-diagrams 1 - 5 .”),
wherein the computer program instruction is further configured to, when executed by the processor:
determine the second lower limb control parameter of the robot according to the reference data and the actual data … in a case that the actual attitude is the flight phase (See at least Fig 1B item Flight: Desired Entry, Actual Entry, Entry():Record data, Fig 1B shows Actual data is collected during Flight, Para [0067] “where, Rfoot is a posture matrix of the sole of the robot…”, Para [0047] “In which, in the during stage of the acceleration phase, the robot will keep performing ground-leaving detections. When changing from the acceleration phase to the flight phase, due to the tracking error of the motion of the robot … The robot first enters from the acceleration phase to the flight phase according to the centroid acceleration planning trajectory. According to the centroid acceleration planning trajectory, the planned transiting time of the robot to change from the acceleration phase to the flight phase can be obtained, so as to determine whether the planned transiting time has come.”, Para [0049] “In which, when the robot has actually entered the flight phase, the theoretical value of the vertical force between the sole of the robot and the ground is zero. In actual applications, the force F.sub.z between sole and ground rapidly reduced to around zero, and a threshold can be used for determining whether the robot gets into the flight phase…”); and
wherein the computer program instruction is further configured to, when executed by the processor:
control the plurality of lower limb joints of the robot according to the first lower limb control parameter or the second lower limb control parameter (See at least Fig 2- Fig 5 shows a plurality of lower limb joints of the robot are being controlled, Para [0030], Para [0031], Para [0032] “The single-legged robot 100 adopts the finite state machine in the above-mentioned legged robot continuous hopping control method. Each state (i.e., the phase) of the single-legged robot 100 is divided into the desired entry stage, the actual entry stage, the during stage, and the exit and state transiting stage. During the hop of the single-legged robot 100 , the state information of the single-legged robot 100 can be updated in real time. The required state information is output to the planning and control unit so as to generate motion control instructions for the actuators. Consequently, the robot is able to hop in different patterns (e.g., height and trajectory) upon given the required state information. FIG. 3 is a schematic diagram of the processes of the continuous hops of different heights performed by the single-legged robot in the embodiment of FIG. 2. As shown in FIG. 3, at the hopping process of sub-diagrams 6 - 10 , the robot realizes the continuous hop of different height from the hopping process of sub-diagrams 1 - 5 .”, Para [0029] “… In the first control cycle, the desired entry stage and the actual entry stage in the acceleration phase coincide with each other, and a timer starts timing. After the second control cycle, it enters the during phase in the acceleration phase, and detects an event triggered in the acceleration phase. In which, the event in the acceleration phase is defined as that the robot has reached a start-hopping height. If the event is triggered (i.e., the robot is determined to have reached the start-hopping height), it enters the exit and state transiting stage in the current control cycle and enters the desired entry stage of the flight phase in the next control cycle; otherwise, it retains in the during stage of the acceleration phase and the timer is increased by 1 time unit of the control cycle. After it enters the flight phase, the first control cycle is in the desired entry stage, and it enters the during stage after the second control cycle…”) …
Although Wang teaches when changing from the acceleration phase to the flight phase, due to the tracking error of the motion of the robot, the robot has a planned ground-leaving time and an actual ground-leaving time, and the two times are often different, where the actual ground-leaving time of the robot is usually the later (See at least Para [0047]), however, he does not explicitly spell out …
with tracking foot-down points of feet ends as a target … with tracking a barycenter line momentum and an upper body attitude as the target …
the computer program instruction is further configured to, when executed by the processor:
determine a barycenter velocity error of the robot in a target
direction according to the reference data and the actual data, wherein the barycenter velocity error is used for adjusting positions of the foot-down points relative to a barycenter; and
determine the second lower limb control parameter according to reference positions
and reference velocities of a plurality of lower limb joints in the reference data and the barycenter velocity error, wherein the second lower limb control parameter comprises control parameters corresponding to the plurality of lower limb joints;
wherein the computer program instruction is further configured to, when executed by the processor:
determine a reference barycenter line momentum and a reference barycenter
position according to the reference data
determine an actual barycenter line momentum and an actual barycenter position
according to the actual data
determine a first external force of a first foot bottom and a second external force of a
second foot bottom of the robot according to a barycenter line momentum tracking control law and a tracking control law of the upper body attitude based on the reference barycenter line momentum, the reference barycenter position, the actual barycenter line momentum and the actual barycenter position; and
determine the first lower limb control parameter according to the first external force
and the second external force, wherein the first lower limb control parameter comprising the control parameters corresponding to the plurality of lower limb joints.
Doi teaches …
with tracking foot-down points of feet ends as a target (See at least Para [0028] “… For example, it is assumed that the robot 100 moves with a hand or foot in contact with a predetermined environmental position, and the memory stores the posture and position of each contact point at that time.”)…
the computer program instruction is further configured to, when executed by the processor:
determine a barycenter velocity error of the robot in a target direction according to
the reference data and the actual data, wherein the barycenter velocity error is used for adjusting positions of the foot-down points relative to a barycenter (See at least Para [0018] “…Furthermore, by integrating the translational acceleration of the center of gravity G including this error, the error may be accumulated and the position and speed of the center of gravity may become an estimated value deviated from the true value.”); and
determine the second lower limb control parameter according to reference positions
and reference velocities of a plurality of lower limb joints in the reference data and the barycenter velocity error, wherein the second lower limb control parameter comprises control parameters corresponding to the plurality of lower limb joints (See at least Para [0008] “… The center-of-gravity estimation device is mounted on, for example, a robot. The robot can accurately control the contact force acting on each contact point between the hand or foot and the environment based on the position of gravity and the speed of the robot estimated by the gravity center estimation device.”, Para [0010] “(1) Contact Point Planning When performing a series of tasks set, the trajectory generation unit calculates the position and orientation (time-series contact point information) of the contact point between the environment and the hand or foot of the robot…”, Para [0018] “…Furthermore, by integrating the translational acceleration of the center of gravity G including this error, the error may be accumulated and the position and speed of the center of gravity may become an estimated value deviated from the true value.”);
Therefore, it would have been obvious to one of the ordinary skill in the art before the
effective filing date of the claimed invention to combine the method of Wang with the teachings of Doi and include the feature of tracking foot-down points of feet ends, determining a barycenter velocity error of the robot in a target direction according to the reference data and the actual data, wherein the barycenter velocity error is used for adjusting positions of the foot-down points relative to a barycenter and determining the second lower limb control parameter according to reference positions and reference velocities of a plurality of lower limb joints in the reference data and the barycenter velocity error, wherein the second lower limb control parameter comprises control parameters corresponding to the plurality of lower limb joints, thereby provide improved stability (See at least Para [0011] “(2) Center of Gravity Trajectory Generation The trajectory generation unit generates a center of gravity trajectory of the robot 100 that can maintain its stability until a predetermined time has elapsed with the current state as an initial state, based on the planned time-series contact point information…”).
Wu teaches … with tracking a barycenter line momentum and an upper body attitude as the target (Page 3 Para 7 “S2.1: Take the attitude angle θ, the position p of the center of mass of the robot, the angular momentum Lcom of the center of mass, and the momentum Pcom of the center of mass line of the robot as the state variable x, x=[θ, p, Lcom, Pcom]T, and take the control variable u as Supporting leg sole force f and moment τ, u=[f,τ]T”)…
wherein the computer program instruction is further configured to, when executed by the processor:
determine a reference barycenter line momentum and a reference barycenter position according to the reference data (See at least Page 3 Para 7 “S2.1: Take the attitude angle θ, the position p of the center of mass of the robot, the angular momentum Lcom of the center of mass, and the momentum Pcom of the center of mass line of the robot as the state variable x, x=[θ, p, Lcom, Pcom]T, and take the control variable u as Supporting leg sole force f and moment τ, u=[f,τ]T”);
determine an actual barycenter line momentum and an actual barycenter position according to the actual data (See at least Page 3 Para 7 “S2.1: Take the attitude angle θ, the position p of the center of mass of the robot, the angular momentum Lcom of the center of mass, and the momentum Pcom of the center of mass line of the robot as the state variable x, x=[θ, p, Lcom, Pcom]T, and take the control variable u as Supporting leg sole force f and moment τ, u=[f,τ]T”);
determine a first external force of a first foot bottom and a second external force of a second foot bottom of the robot according to a barycenter line momentum tracking control law and a tracking control law of the upper body attitude based on the reference barycenter line momentum, the reference barycenter position, the actual barycenter line momentum and the actual barycenter position (See at least Page 3 Para 7 “S2.1: Take the attitude angle θ, the position p of the center of mass of the robot, the angular momentum Lcom of the center of mass, and the momentum Pcom of the center of mass line of the robot as the state variable x, x=[θ, p, Lcom, Pcom]T, and take the control variable u as Supporting leg sole force f and moment τ, u=[f,τ]T”); and
determine the first lower limb control parameter according to the first external force and the second external force, wherein the first lower limb control parameter comprises the control parameters corresponding to the plurality of lower limb joints (See at least Page 3 Para 7 “S2.1: Take the attitude angle θ, the position p of the center of mass of the robot, the angular momentum Lcom of the center of mass, and the momentum Pcom of the center of mass line of the robot as the state variable x, x=[θ, p, Lcom, Pcom]T, and take the control variable u as Supporting leg sole force f and moment τ of the supporting leg sole force f and moment τ, u=[f,τ]T”).
Therefore, it would have been obvious to one of ordinary skill, in the art before the effective filing date of the claimed invention to combine the method of Wang with the teachings of Wu and include the feature of determining the first lower limb control parameter according to the first external force and the second external force, the first lower limb control parameter including control parameters corresponding to a plurality of lower limb joints using a tracking control law of the upper body attitude based on the reference barycenter line momentum, the reference barycenter position, the actual barycenter line momentum and the actual barycenter position, thereby improve the stability of the robot when walking (See at least Page 4 Para 18 “The beneficial effects of the present invention are: compared with the humanoid model predictive control scheme in the prior art, the present invention not only improves the modeling accuracy, but also ensures the stability of the controller, and the overall control method of the present invention has better generality adaptability and robustness.”).
Regarding Claim 21, modified Wang teaches all the elements of claim 1. Wang further teaches … according to the reference data and the actual data (See at least Fig 1B item Flight: Desired Entry, Actual Entry, Entry():Record data)…
However, Wang does not explicitly spell out the method for controlling the robot according to
claim 1, further comprising:
determining a second target control parameter of the robot with tracking a barycenter angular momentum and positions and velocities of a plurality of upper limb joints as the target …; and
controlling the robot according to the first target control parameter comprises:
controlling the robot according to the first target control parameter and the second target control parameter, wherein the first target control parameter comprises control parameters corresponding to the plurality of lower limb joints of the robot, and the second target control parameter comprises control parameters corresponding to the plurality of upper limb joints of the robot.
Doi teaches the method for controlling the robot according to claim 1, further comprising:
determining a second target control parameter of the robot with tracking a barycenter angular momentum and positions and velocities of a plurality of upper limb joints as the target (See at least Para [0005] “Angular motion calculation means for calculating the angular momentum of the surroundings, force of each contact point detected by the force detection means, posture and position of each contact point acquired by the acquisition means Providing first estimating means for estimating at least one of the gravity center position and the velocity of the robot using a Kalman filter on the basis of the angular momentum around the gravity center calculated by the angular motion calculation means, and It is a center-of-gravity estimation device that is a feature. In this aspect, the first estimation unit calculates the force of each contact point detected by the force detection unit, the posture and position of each contact point acquired by the acquisition unit, and the angular motion calculation unit A Kalman filter for a state equation using the position and velocity of the center of gravity of the robot as a state variable, and an observation equation using the angular momentum around the center of gravity of the robot based on the angular momentum around the center of gravity Is applied to estimate the position and velocity of the center of gravity of the robot,”) … ; and
controlling the robot according to the first target control parameter comprises:
controlling the robot according to the first target control parameter and the second target control parameter, wherein the first target control parameter comprises control parameters corresponding to the plurality of lower limb joints of the robot, and the second target control parameter comprises control parameters corresponding to the plurality of upper limb joints of the robot (See at least Para [0012] “(3) Contact Force Control The control unit performs force control of each joint of the robot 100 such that the contact force calculated by the trajectory generation unit is generated at each contact point.”, Para [0013] “(4) Whole Body Coordination The trajectory generation unit corrects the gravity center trajectory based on the result of the force control of the control unit. The control unit calculates the posture of the whole body of the robot 100 and each joint angle based on the gravity center trajectory corrected by the trajectory generation unit, and controls the robot 100.”, Para [0010] “(1) Contact Point Planning When performing a series of tasks set, the trajectory generation unit calculates the position and orientation (time-series contact point information) of the contact point between the environment and the hand or foot of the robot. For example, as shown in FIG. 1, the robot 100 moves to the front of a desk while bringing a hand into contact with a wall, and performs a task of holding a pet bottle at the back while bringing a hand into contact with the desk. At this time, the trajectory generation unit is set by the operation planning software (planner) or the user in advance to which position the hand, foot, etc. are to be brought into contact with the robot 100 to support the torso.”).
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective
filing date of the claimed invention to combine the method of Wang with the teachings of Doi and include the feature of determining a second target control parameter of the robot with tracking a barycenter angular momentum and positions and velocities of a plurality of upper limb joints as the target and controlling the robot according to the first target control parameter and the second target control parameter, wherein the first target control parameter comprises control parameters corresponding to the plurality of lower limb joints of the robot, and the second target control parameter comprises control parameters corresponding to the plurality of upper limb joints of the robot, thereby provide improved stability (See at least Para [0011] “(2) Center of Gravity Trajectory Generation The trajectory generation unit generates a center of gravity trajectory of the robot 100 that can maintain its stability until a predetermined time has elapsed with the current state as an initial state, based on the planned time-series contact point information…”).
Regarding Claim 22, modified Wang teaches all the elements of claim 9. Wang further teaches … according to the reference data and the actual data (See at least Fig 1B item Flight: Desired Entry, Actual Entry, Entry():Record data)…
However, Wang does not explicitly spell out the electronic device according to
claim 9, wherein the processor is further configured to:
determine a second target control parameter of the robot with tracking a barycenter angular momentum and positions and velocities of a plurality of upper limb joints as the target …; and
control the robot according to the first target control parameter and the second target control parameter, wherein the first target control parameter comprises control parameters corresponding to the plurality of lower limb joints of the robot, and the second target control parameter comprises control parameters corresponding to the plurality of upper limb joints of the robot.
Doi teaches the electronic device according to claim 9, wherein the processor is further
configured to:
determine a second target control parameter of the robot with tracking a barycenter angular momentum and positions and velocities of a plurality of upper limb joints as the target (See at least Para [0005] “Angular motion calculation means for calculating the angular momentum of the surroundings, force of each contact point detected by the force detection means, posture and position of each contact point acquired by the acquisition means Providing first estimating means for estimating at least one of the gravity center position and the velocity of the robot using a Kalman filter on the basis of the angular momentum around the gravity center calculated by the angular motion calculation means, and It is a center-of-gravity estimation device that is a feature. In this aspect, the first estimation unit calculates the force of each contact point detected by the force detection unit, the posture and position of each contact point acquired by the acquisition unit, and the angular motion calculation unit A Kalman filter for a state equation using the position and velocity of the center of gravity of the robot as a state variable, and an observation equation using the angular momentum around the center of gravity of the robot based on the angular momentum around the center of gravity Is applied to estimate the position and velocity of the center of gravity of the robot,”) …; and
control the robot according to the first target control parameter and the second target control parameter, wherein the first target control parameter comprises control parameters corresponding to the plurality of lower limb joints of the robot, and the second target control parameter comprises control parameters corresponding to the plurality of upper limb joints of the robot (See at least Para [0012] “(3) Contact Force Control The control unit performs force control of each joint of the robot 100 such that the contact force calculated by the trajectory generation unit is generated at each contact point.”, Para [0013] “(4) Whole Body Coordination The trajectory generation unit corrects the gravity center trajectory based on the result of the force control of the control unit. The control unit calculates the posture of the whole body of the robot 100 and each joint angle based on the gravity center trajectory corrected by the trajectory generation unit, and controls the robot 100.”, Para [0010] “(1) Contact Point Planning When performing a series of tasks set, the trajectory generation unit calculates the position and orientation (time-series contact point information) of the contact point between the environment and the hand or foot of the robot. For example, as shown in FIG. 1, the robot 100 moves to the front of a desk while bringing a hand into contact with a wall, and performs a task of holding a pet bottle at the back while bringing a hand into contact with the desk. At this time, the trajectory generation unit is set by the operation planning software (planner) or the user in advance to which position the hand, foot, etc. are to be brought into contact with the robot 100 to support the torso.”).
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective
filing date of the claimed invention to combine the method of Wang with the teachings of Doi and include the feature of determining a second target control parameter of the robot with tracking a barycenter angular momentum and positions and velocities of a plurality of upper limb joints as the target and controlling the robot according to the first target control parameter and the second target control parameter, wherein the first target control parameter comprises control parameters corresponding to the plurality of lower limb joints of the robot, and the second target control parameter comprises control parameters corresponding to the plurality of upper limb joints of the robot, thereby provide improved stability (See at least Para [0011] “(2) Center of Gravity Trajectory Generation The trajectory generation unit generates a center of gravity trajectory of the robot 100 that can maintain its stability until a predetermined time has elapsed with the current state as an initial state, based on the planned time-series contact point information…”).
11. Claim(s) 2, 10, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. (US20210221455A1) (Hereinafter Wang) in view of Doi et al. (JP2015208790A) (Hereinafter Doi), Wu et al. (CN115202378A) (Hereinafter Wu), and further in view of Lindgren et al. (US 2024/0317510 A1) (Hereinafter Lindgren).
12. Regarding Claim 2, modified Wang teaches all the elements of claim 1. Wang further teaches the method for controlling the robot according to claim 1, wherein the actual data comprises a first support force of a first foot bottom and a second support force of a second foot bottom (See at least Para [0003] “During the walking of a legged robot, the program (of the control system) of the robot will determine whether the robot is the states of supported by one leg or two legs based on sensor information of the robot, and output a status determination result to a control planning algorithm to perform the corresponding operation, that is, to use a finite state machine suitable for walking…”, Fig 1B shows Event 2 determine whether being landed by checking force which is construed as the actual data, Para [0023] “S 120 : obtaining a state detecting result by detecting in the acceleration phase whether a height of a centroid of the robot reaches a start-hopping height, detecting in the flight phase whether an end force of a foot of one of the legs of the robot is greater than a threshold to suddenly change…”, Para [0024] “When it transits between the four stages of each phase and between the adjacent phases, the corresponding states of the robot are different. In which, the transition is driven by the trigger of an event such as the force upon a sole of the robot being greater than a threshold in the flight phase. If the force is greater than the threshold, it means that the robot is landed, and it enters the exit and state transiting stage of the flight phase in the current control cycle and enters the deceleration phase in the next cycle.”); and
determining the actual attitude of the robot according to the actual data comprises: determining the actual attitude of the robot as the support phase in response to determining that … one of the first support force and the second support force is greater than or equal to a first preset threshold value (See at least Para [0024] “When it transits between the four stages of each phase and between the adjacent phases, the corresponding states of the robot are different. In which, the transition is driven by the trigger of an event such as the force upon a sole of the robot being greater than a threshold in the flight phase. If the force is greater than the threshold, it means that the robot is landed, and it enters the exit and state transiting stage of the flight phase in the current control cycle and enters the deceleration phase in the next cycle.”, Para [0056] “7) determining the robot as having entered the exit and state transiting stage of the flight phase and going to enter the desired entry stage and the actual entry stage of the deceleration phase in the next control cycle, if the changing direction of the vertical force is gradually increasing and the vertical force is greater than or equal to a second preset action force threshold.”); and
determining the actual attitude of the robot as the flight phase in response to determining that a larger one of the first support force and the second support force is smaller than or equal to a second preset threshold value (See at least Para [0052] “5) determining the robot as having entered the actual entry stage of the flight phase, and going to be in the during stage in the flight phase in the next control cycle, if the changing direction of the vertical force is gradually decreasing and the vertical force is smaller than or equal to the first preset action force threshold.”) and a duration that the support phase lasts for is greater than or equal to a preset time threshold value (See at least Para [0046] “3) obtaining a planned transiting time of the robot to transit from the acceleration phase to the flight phase according to a centroid acceleration planning trajectory, determining whether the planned transiting time is up, and determining the robot as having entered the exit and state transiting stage of the acceleration phase if the planned transiting time is up and going to enter the desired entry stage of the flight phase in a next control cycle of the robot.”, discloses determining whether the planned transiting time is up which is construed as a duration that the support phase lasts for is greater than or equal to a preset time threshold value, Para [0047] “…According to the centroid acceleration planning trajectory, the planned transiting time of the robot to change from the acceleration phase to the flight phase can be obtained, so as to determine whether the planned transiting time has come. When the planned transiting time comes, it determines that the robot has entered the exit and state transiting stage of the acceleration phase, and enters the desired entry phase of the flight phase in the next control cycle after the exit and state transiting stage of the acceleration phase ends.”).
However, Wang does not explicitly spell out … a smaller one of the first support force and the second support force …
Lindgren teaches … a smaller one of the force is selected (See at least Para [0158] “This has the advantage that this allows a smaller gripping force to be selected…”)…
Therefore, it would have been obvious to one of ordinary skill, in the art before the effective filing date of the claimed invention to combine the method of Wang with the teachings of Lindgren and include the feature of selecting a smaller force, thereby providing accuracy and efficiency (See at least Para [0010] “Moreover, the automation of the mounting of insulating elements on structural elements has the advantage that this can reduce the risk of incorrect manipulations…”, Para [0012] “The system proposed here also offers the particular advantage that automation can be made much more efficient and inexpensive…”).
13. Regarding Claim 10, modified Wang teaches all the elements of claim 9. Wang further teaches the electronic device according to claim 9, wherein the actual data comprises a first support force of a first foot bottom and a second support force of a second foot bottom (See at least Para [0003] “During the walking of a legged robot, the program (of the control system) of the robot will determine whether the robot is the states of supported by one leg or two legs based on sensor information of the robot, and output a status determination result to a control planning algorithm to perform the corresponding operation, that is, to use a finite state machine suitable for walking…”, Fig 1B shows Event 2 determine whether being landed by checking force which is construed as the actual data, Para [0023] “S 120 : obtaining a state detecting result by detecting in the acceleration phase whether a height of a centroid of the robot reaches a start-hopping height, detecting in the flight phase whether an end force of a foot of one of the legs of the robot is greater than a threshold to suddenly change…”, Para [0024] “When it transits between the four stages of each phase and between the adjacent phases, the corresponding states of the robot are different. In which, the transition is driven by the trigger of an event such as the force upon a sole of the robot being greater than a threshold in the flight phase. If the force is greater than the threshold, it means that the robot is landed, and it enters the exit and state transiting stage of the flight phase in the current control cycle and enters the deceleration phase in the next cycle.”); and
The processor is further configured to:
determine the actual attitude of the robot according to the actual data comprises: determining the actual attitude of the robot as the support phase in response to determining
that … one of the first support force and the second support force is greater than or equal to a first preset threshold value (See at least Para [0024] “When it transits between the four stages of each phase and between the adjacent phases, the corresponding states of the robot are different. In which, the transition is driven by the trigger of an event such as the force upon a sole of the robot being greater than a threshold in the flight phase. If the force is greater than the threshold, it means that the robot is landed, and it enters the exit and state transiting stage of the flight phase in the current control cycle and enters the deceleration phase in the next cycle.”, Para [0056] “7) determining the robot as having entered the exit and state transiting stage of the flight phase and going to enter the desired entry stage and the actual entry stage of the deceleration phase in the next control cycle, if the changing direction of the vertical force is gradually increasing and the vertical force is greater than or equal to a second preset action force threshold.”); and
determine the actual attitude of the robot as the flight phase in response to determining that a larger one of the first support force and the second support force is smaller than or equal to a second preset threshold value (See at least Para [0052] “5) determining the robot as having entered the actual entry stage of the flight phase, and going to be in the during stage in the flight phase in the next control cycle, if the changing direction of the vertical force is gradually decreasing and the vertical force is smaller than or equal to the first preset action force threshold.”) and a duration that the support phase lasts for is greater than or equal to a preset time threshold value (See at least Para [0046] “3) obtaining a planned transiting time of the robot to transit from the acceleration phase to the flight phase according to a centroid acceleration planning trajectory, determining whether the planned transiting time is up, and determining the robot as having entered the exit and state transiting stage of the acceleration phase if the planned transiting time is up and going to enter the desired entry stage of the flight phase in a next control cycle of the robot.”, discloses determining whether the planned transiting time is up which is construed as a duration that the support phase lasts for is greater than or equal to a preset time threshold value, Para [0047] “…According to the centroid acceleration planning trajectory, the planned transiting time of the robot to change from the acceleration phase to the flight phase can be obtained, so as to determine whether the planned transiting time has come. When the planned transiting time comes, it determines that the robot has entered the exit and state transiting stage of the acceleration phase, and enters the desired entry phase of the flight phase in the next control cycle after the exit and state transiting stage of the acceleration phase ends.”).
However, Wang does not explicitly spell out … a smaller one of the first support force and the second support force …
Lindgren teaches … a smaller one of the force is selected (See at least Para [0158] “This has the advantage that this allows a smaller gripping force to be selected…”)…
Therefore, it would have been obvious to one of ordinary skill, in the art before the effective filing date of the claimed invention to combine the method of Wang with the teachings of Lindgren and include the feature of selecting a smaller force, thereby providing accuracy and efficiency (See at least Para [0010] “Moreover, the automation of the mounting of insulating elements on structural elements has the advantage that this can reduce the risk of incorrect manipulations…”, Para [0012] “The system proposed here also offers the particular advantage that automation can be made much more efficient and inexpensive…”).
14. Regarding Claim 18, modified Wang teaches all the non-transitory computer-readable storage medium according to claim 17, wherein the actual data comprise a first support force of a first foot bottom and a second support force of a second foot bottom (See at least Para [0003] “During the walking of a legged robot, the program (of the control system) of the robot will determine whether the robot is the states of supported by one leg or two legs based on sensor information of the robot, and output a status determination result to a control planning algorithm to perform the corresponding operation, that is, to use a finite state machine suitable for walking…”, Fig 1B shows Event 2 determine whether being landed by checking force which is construed as the actual data, Para [0023] “S 120 : obtaining a state detecting result by detecting in the acceleration phase whether a height of a centroid of the robot reaches a start-hopping height, detecting in the flight phase whether an end force of a foot of one of the legs of the robot is greater than a threshold to suddenly change…”, Para [0024] “When it transits between the four stages of each phase and between the adjacent phases, the corresponding states of the robot are different. In which, the transition is driven by the trigger of an event such as the force upon a sole of the robot being greater than a threshold in the flight phase. If the force is greater than the threshold, it means that the robot is landed, and it enters the exit and state transiting stage of the flight phase in the current control cycle and enters the deceleration phase in the next cycle.”); and
the computer program instruction is further configured to, when executed by the processor:
determine the actual attitude of the robot according to the actual data comprises: determining the actual attitude of the robot as the support phase in response to determining that … one of the first support force and the second support force is greater than or equal to a first preset threshold value (See at least Para [0024] “When it transits between the four stages of each phase and between the adjacent phases, the corresponding states of the robot are different. In which, the transition is driven by the trigger of an event such as the force upon a sole of the robot being greater than a threshold in the flight phase. If the force is greater than the threshold, it means that the robot is landed, and it enters the exit and state transiting stage of the flight phase in the current control cycle and enters the deceleration phase in the next cycle.”, Para [0056] “7) determining the robot as having entered the exit and state transiting stage of the flight phase and going to enter the desired entry stage and the actual entry stage of the deceleration phase in the next control cycle, if the changing direction of the vertical force is gradually increasing and the vertical force is greater than or equal to a second preset action force threshold.”); and
determine the actual attitude of the robot as the flight phase in response to determining that a larger one of the first support force and the second support force is smaller than or equal to a second preset threshold value (See at least Para [0052] “5) determining the robot as having entered the actual entry stage of the flight phase, and going to be in the during stage in the flight phase in the next control cycle, if the changing direction of the vertical force is gradually decreasing and the vertical force is smaller than or equal to the first preset action force threshold.”) and a duration that the support phase lasts for is greater than or equal to a preset time threshold value (See at least Para [0046] “3) obtaining a planned transiting time of the robot to transit from the acceleration phase to the flight phase according to a centroid acceleration planning trajectory, determining whether the planned transiting time is up, and determining the robot as having entered the exit and state transiting stage of the acceleration phase if the planned transiting time is up and going to enter the desired entry stage of the flight phase in a next control cycle of the robot.”, discloses determining whether the planned transiting time is up which is construed as a duration that the support phase lasts for is greater than or equal to a preset time threshold value, Para [0047] “…According to the centroid acceleration planning trajectory, the planned transiting time of the robot to change from the acceleration phase to the flight phase can be obtained, so as to determine whether the planned transiting time has come. When the planned transiting time comes, it determines that the robot has entered the exit and state transiting stage of the acceleration phase, and enters the desired entry phase of the flight phase in the next control cycle after the exit and state transiting stage of the acceleration phase ends.”).
However, Wang does not explicitly spell out … a smaller one of the first support force and the second support force …
Lindgren teaches … a smaller one of the force is selected (See at least Para [0158] “This has the advantage that this allows a smaller gripping force to be selected…”)…
Therefore, it would have been obvious to one of ordinary skill, in the art before the effective filing date of the claimed invention to combine the method of Wang with the teachings of Lindgren and include the feature of selecting a smaller force, thereby providing accuracy and efficiency (See at least Para [0010] “Moreover, the automation of the mounting of insulating elements on structural elements has the advantage that this can reduce the risk of incorrect manipulations…”, Para [0012] “The system proposed here also offers the particular advantage that automation can be made much more efficient and inexpensive…”).
22. Claim(s) 8 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. (US2021221455A1) (Hereinafter Wang) in view of Doi et al. (JP2015208790A) (Hereinafter Doi), Wu et al. (CN115202378A) (Hereinafter Wu), Otani et al. (Otani T, Hashimoto K, Miyamae S, Ueta H, Natsuhara A, Sakaguchi M, Kawakami Y, Lim H-O, Takanishi A. Upper-Body Control and Mechanism of Humanoids to Compensate for Angular Momentum in the Yaw Direction Based on Human Running. Applied Sciences. 2018; 8(1):44. https://doi.org/10.3390/app8010044) (Hereinafter Otani), and further in view Gao et al. (Gao Z, Chen X, Yu Z, Han L, Zhang J, Huang G. Hybrid Momentum Compensation Control by Using Arms for Bipedal Dynamic Walking. Biomimetics (Basel). 2023 Jan 12;8(1):31. doi: 10.3390/biomimetics8010031. PMID: 36648817; PMCID: PMC9844417.) (Hereinafter Gao).
23. Regarding Claim 8, modified Wang teaches all the elements of claim 21.
However, Wang does not explicitly spell out the method for controlling the robot according to claim 21, wherein
determining the second target control parameter of the robot with tracking the barycenter angular momentum and the positions and the velocities of the plurality of upper limb joints as the target according to the reference data and the actual data comprises:
determining a reference barycenter angular momentum, and reference positions and reference velocities of the plurality of upper limb joints according to the reference data;
determining an actual barycenter angular momentum and actual positions and actual velocities of the plurality of upper limb joints according to the actual data; and
determining the second target control parameter according to the reference barycenter angular momentum, the reference positions and the reference velocities of the plurality of upper limb joints, the actual barycenter angular momentum, and the actual positions and the actual velocities of the plurality of upper limb joints.
Otani teaches … determining the second target control parameter according to the reference barycenter angular momentum, the reference positions and the reference velocities of the plurality of upper limb joints, the actual barycenter angular momentum, and the actual positions and the actual velocities of the plurality of upper limb joints (See at least Page 5 “2.2. Upper-Body Control Method Based on Angular Momentum - … In this paper, we present all vectors of position, angular velocity, linear momentum and angular momentum, and all rotation matrices in the Cartesian frame fixed on the ground. The inertia matrix is basically with respect to the center of mass position of the link presented in the Cartesian frame fixed on the ground.”, Page 6 “The gain should be determined by the desired motion and the capacity of generating the angular momentum by each part of the robot.”).
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective
filing date of the claimed invention to combine the teachings of Wang with the teachings of Otani and include the feature of determining another target control parameter of the robot according to the reference barycenter angular momentum, the reference positions and the reference velocities of the plurality of upper limb joints, the actual barycenter angular momentum, and the actual positions and the actual velocities of the plurality of upper limb joints, thereby improving stability of the robot (See at least Page 14 Para 2 “Thanks to improved stability, humanoids will be able to advance into human living spaces and work stably.”).
Gao teaches the method for controlling the robot according to claim 1, wherein
determining the second target control parameter of the robot with tracking the barycenter angular momentum and the positions and the velocities of the plurality of upper limb joints as the target according to the reference data and the actual data comprises:
determining a reference barycenter angular momentum, and reference positions and reference velocities of the plurality of upper limb joints according to the reference data (Page 11 Figure 7, “Figure7.The images on the (left, right) show the reference angle (dark red dashed line),the actual angles(solid orange lines)of the right arm and the left arm shoulder, and the corresponding left and right leg hip joint pitch angles(solid blue lines),respectively. The black dash-dotted line box, the purple dash-dotted box, and the green dash-dotted box within the same color range indicate the associated changes.”, Page 12 Figure 8 “Figure 8. The images on the left and right show the reference angular velocity (dark red dashed lines), Figure 8. The images on the (left, right) show the reference angular velocity (dark red dashed lines), the actual angular velocities (solid orange lines) of the right arm and the left arm shoulder, and their the actual angular velocities (solid orange lines) of the right arm and the left arm shoulder, and their corresponding left and right leg hip joint pitch angular velocities (solid blue lines), respectively. corresponding left and right leg hip joint pitch angular velocities (solid blue lines), respectively”);
determining an actual barycenter angular momentum and actual positions and actual velocities of the plurality of upper limb joints according to the actual data (Page 11 Figure 7, “Figure7.The images on the (left, right) show the reference angle (dark red dashed line),the actual angles(solid orange lines)of the right arm and the left arm shoulder, and the corresponding left and right leg hip joint pitch angles(solid blue lines),respectively. The black dash-dotted line box, the purple dash-dotted box, and the green dash-dotted box within the same color range indicate the associated changes.”, Page 12 Figure 8 “Figure 8. The images on the left and right show the reference angular velocity (dark red dashed lines), Figure 8. The images on the (left, right) show the reference angular velocity (dark red dashed lines), the actual angular velocities (solid orange lines) of the right arm and the left arm shoulder, and their the actual angular velocities (solid orange lines) of the right arm and the left arm shoulder, and their corresponding left and right leg hip joint pitch angular velocities (solid blue lines), respectively. corresponding left and right leg hip joint pitch angular velocities (solid blue lines), respectively”); and …
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective
filing date of the claimed invention to combine the method of Wang with the teachings of Otani and include the feature of determining both reference and actual barycenter angular momentum, positions, velocities of the plurality of upper limb joints according to both the reference and actual data, thereby improve stability of the robot, thus safety of the environment where the robot operates (Page 12 “5. Conclusions - Based on the basic mechanism of human motion, the biped robot is designed to walk Based on the basic mechanism of human motion, the biped robot is designed to walk stably in a human environment, particularly after being disturbed, which represents the stably in a human environment, particularly after being disturbed, which represents the basic problem that affects its practical application. In this article, we make full use of the basic problem that affects its practical application…”).
24. Regarding Claim 16, modified Wang teaches all the elements of claim 22.
However, Wang does not explicitly spell out the electronic device according to claim 22, wherein the processor is further configured to:
determine a reference barycenter angular momentum, and reference positions and reference velocities of the plurality of upper limb joints according to the reference data;
determine an actual barycenter angular momentum and actual positions and actual velocities of the plurality of upper limb joints according to the actual data; and
determine the second target control parameter according to the reference barycenter angular momentum, the reference positions and the reference velocities of the plurality of upper limb joints, the actual barycenter angular momentum, and the actual positions and the actual velocities of the plurality of upper limb joints.
Otani teaches … determine the second target control parameter according to the reference barycenter angular momentum, the reference positions and the reference velocities of the plurality of upper limb joints, the actual barycenter angular momentum, and the actual positions and the actual velocities of the plurality of upper limb joints (See at least Page 5 “2.2. Upper-Body Control Method Based on Angular Momentum - … In this paper, we present all vectors of position, angular velocity, linear momentum and angular momentum, and all rotation matrices in the Cartesian frame fixed on the ground. The inertia matrix is basically with respect to the center of mass position of the link presented in the Cartesian frame fixed on the ground.”, Page 6 “The gain should be determined by the desired motion and the capacity of generating the angular momentum by each part of the robot.”).
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective
filing date of the claimed invention to combine the teachings of Wang with the teachings of Otani and include the feature of determining another target control parameter of the robot according to the reference barycenter angular momentum, the reference positions and the reference velocities of the plurality of upper limb joints, the actual barycenter angular momentum, and the actual positions and the actual velocities of the plurality of upper limb joints, thereby improving stability of the robot (See at least Page 14 Para 2 “Thanks to improved stability, humanoids will be able to advance into human living spaces and work stably.”).
Gao teaches the electronic device according to claim 9, wherein the processor is further
configured to:
determine a reference barycenter angular momentum, and reference positions and reference velocities of the plurality of upper limb joints according to the reference data; (Page 11 Figure 7 “Figure7.The images on the (left, right) show the reference angle (dark red dashed line),the actual angles(solid orange lines)of the right arm and the left arm shoulder, and the corresponding left and right leg hip joint pitch angles(solid blue lines),respectively. The black dash-dotted line box, the purple dash-dotted box, and the green dash-dotted box within the same color range indicate the associated changes.”, Page 12 Figure 8 “Figure 8. The images on the left and right show the reference angular velocity (dark red dashed lines), Figure 8. The images on the (left, right) show the reference angular velocity (dark red dashed lines), the actual angular velocities (solid orange lines) of the right arm and the left arm shoulder, and their the actual angular velocities (solid orange lines) of the right arm and the left arm shoulder, and their corresponding left and right leg hip joint pitch angular velocities (solid blue lines), respectively. corresponding left and right leg hip joint pitch angular velocities (solid blue lines), respectively”);
determine an actual barycenter angular momentum and actual positions and actual velocities of the plurality of upper limb joints according to the actual data (Page 11 Figure 7 “Figure7.The images on the (left, right) show the reference angle (dark red dashed line),the actual angles(solid orange lines)of the right arm and the left arm shoulder, and the corresponding left and right leg hip joint pitch angles(solid blue lines),respectively. The black dash-dotted line box, the purple dash-dotted box, and the green dash-dotted box within the same color range indicate the associated changes.”, Page 12 Figure 8 “Figure 8. The images on the left and right show the reference angular velocity (dark red dashed lines), Figure 8. The images on the (left, right) show the reference angular velocity (dark red dashed lines), the actual angular velocities (solid orange lines) of the right arm and the left arm shoulder, and their the actual angular velocities (solid orange lines) of the right arm and the left arm shoulder, and their corresponding left and right leg hip joint pitch angular velocities (solid blue lines), respectively. corresponding left and right leg hip joint pitch angular velocities (solid blue lines), respectively”); and …
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective
filing date of the claimed invention to combine the method of Wang with the teachings of Otani and include the feature of determining both reference and actual barycenter angular momentum, positions, velocities of the plurality of upper limb joints according to both the reference and actual data, thereby improve stability of the robot, thus safety of the environment where the robot operates (Page 12 “5. Conclusions - Based on the basic mechanism of human motion, the biped robot is designed to walk Based on the basic mechanism of human motion, the biped robot is designed to walk stably in a human environment, particularly after being disturbed, which represents the stably in a human environment, particularly after being disturbed, which represents the basic problem that affects its practical application. In this article, we make full use of the basic problem that affects its practical application…”).
Allowable Subject Matter
25. Claims 23, 24, and 25 are objected to as being dependent upon a rejected base claim but would be allowable if rewritten in independent form including all the limitations of the base claim and any intervening claims.
Conclusion
25. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Huang et al. (US 11618519 B2) teaches a method of tracking control for a foot force and moment of a biped robot
26. THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/SHAHEDA HOQUE/
Examiner, Art Unit 3658
/Ramon A. Mercado/Supervisory Patent Examiner, Art Unit 3658
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