DETAILED ACTION
This Office Action is taken in response to Applicant’s Amendment and Remarks filed on
10/10/2025 regarding Application No. 18/251,861 originally filed on 05/04/2023. Claims 1, 8-10, 12-16 are pending for consideration:
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
The applicant argues “Harris … fails to teach or suggest the specific computational architecture claimed in amended Claim 1,” including “calculating a first torque in Cartesian space … converting this … via Jacobian matrix transposition … deriving a third torque through … friction feedforward … and deriving the drive information from … Fs, the third torque, and the second torque,” [Remarks, p. 8-11]. The examiner respectfully disagrees.
Harris discloses of the claimed boundary control context and joint-space torque control using friction compensation/feedforward. (as per “ƒ … are the joint friction vector … τ is the vector … of joint motor torques” in ¶100; as per “It implements a simple PD control algorithm for each joint with gravity, friction and guiding force compensation” in ¶155). Further, the presently applied combination supplies the remaining claimed steps: Huang discloses of the impedance computation in Cartesian space using position deviation, speed deviation, and interaction force (as per ¶20; ¶85), and further discloses mapping the task-space control output into joint-space impedance control torque based on the Jacobian (as per ¶93). Bowling teaches Jacobian-transpose conversion machinery at the current joint configuration and drive command generation using multiple torque/force components. (as per “Force transformer module 362 transforms this scalar to force FINST … a vector of forces and torques …” in ¶193, as per Eqn. 6; as per ¶284–¶288; as per Eqns. 14/19; as per ¶278; ¶282). Thus, the applicant’s arguments are not persuasive.
The applicant argues “Bowling does not fill the gaps left by Harris” and “does not disclose … using an impedance model to calculate a first torque in Cartesian space … [or] converting … via Jacobian transposition … [or] combining Fs, friction-compensated torque, and converted Cartesian-space torque to derive the final drive information,” [Remarks, p. 9-11]. The examiner respectfully disagrees.
Bowling expressly discloses Jacobian-transpose based conversion and producing commanded joint torques for driving joints toward commanded joint angles. (as per ¶193, Eqn. 6; as per ¶284–¶288; as per “inverse dynamics calculation … produces … the torque that should be applied to the joint” in ¶278; as per ¶282). Further, Huang is specifically applied for the impedance-model-based Cartesian/task-space calculation that applicant alleges is missing from Bowling. (as per ¶20; ¶85; ¶89; ¶93). Therefore, when combined as applied, the references collectively teach the claimed impedance computation, Jacobian-transpose based conversion, and drive information derived from the resulting torque components (including friction compensation taught by Harris).
The applicant argues “Huang … relies on either positional feedback or impedance control alone,” “lacks synergistic integration of both real-time kinematic and dynamic feedback loops,” and “does not include explicit friction feedforward terms (f),” [Remarks, p. 10-11]. The examiner respectfully disagrees.
Huang expressly discloses an impedance model that uses position deviation, speed deviation, and the actual interaction force (as per ¶20; ¶85) and then calculates the joint-space impedance control torque from the task-space control amount based on the Jacobian (as per ¶93). Huang further discloses determining a compensation torque for nonlinear dynamics terms and controlling joint torque according to the impedance control torque and the compensation torque (as per ¶97; ¶110). Applicant’s asserted “dual-space iterative refinement,” “single linear compensation path,” and “force-torque hybrid logic” are not required by amended Claim 1. Moreover, Harris expressly teaches friction feedforward/compensation in the joint torque control law. (as per ¶100; ¶155). Thus, the applicant’s arguments are not persuasive.
The applicant argues a person of ordinary skill “would not be motivated” to combine Harris with Bowling and Huang because the references “solve different problems,” and further asserts “unexpected synergy” and “improved stability,” [Remarks, p. 10-12]. The examiner respectfully disagrees.
Harris, Bowling, and Huang each address robot manipulation in the presence of external/environmental forces and teach control to improve compliant interaction. (as per Harris ¶63; ¶83; Bowling ¶9; Huang ¶43; ¶97). A person of ordinary skill would have been motivated to incorporate Huang’s known impedance-model control and Bowling’s Jacobian-transpose drive-command architecture into Harris’s boundary control framework to obtain a predictable improvement in compliant force interaction and stability, with a reasonable expectation of success. Applicant’s “unexpected synergy” assertions are attorney argument not supported by objective evidence. Additionally, amended Claim 1 recites alternative “or” implementations; the applied combination teaches at least the torque-based alternative, which is sufficient to meet the limitation.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
“navigation device configured to” in claim 13
“control device configured to” in claim 13
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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, 8-10, 12-16 are rejected under 35 U.S.C. 103 as being unpatentable over Harris (US Pub. No. 20040128026) in view of Bowling (US Pub. No. 20140039681) in further view of Huang (WO Pub. No. 2022007358).
As per Claim 1, Harris discloses comprising a surgical robot comprising a manipulation terminal (as per Fig. 2), comprising:
defining a safe zone and a warning boundary outside the safe zone, based on edge information of a surgical object; (as per “a flat plane and an outline tunnel, which is defined by a series of co-ordinates around its outline, could define the constraint region, with the proximity to the plane being computed from the plane equation, and the proximity to the tunnel being computed by searching the co-ordinate list to find the nearest matching outline segment. With this control system, as the surgeon moves the cutter tool closer to a boundary, the robot would be stiffened and the resistance increased” in ¶85, as per “The determination of the intersection with the NURBS surface allows for a more accurate determination as to whether a restraining force needs to be applied near a constraint boundary” in ¶90, as per “The tool tip P is represented by a ball on the end of a shaft. For a complex surface, a ball-ended or acorn-type tool would be used rather than the barrel cutter used for flat plane cutting. A force vector V, indicating the direction in which the surgeon is applying force, is projected from the tool tip P through the NURBS surface S.” in ¶92)
based on a distance function between a current position and posture of the manipulation terminal and the warning boundary, (as per “The boundary controller in the main control loop monitors the Cartesian position X of the cutter relative to the boundary of the safe region. It changes the gains of the position controller, and sets the position demand according to the minimum distance between the cutter and the boundary” in ¶63, as per “Region II (RII) is an area near the boundary. The boundary controller increases the position control gains and decreases the admittance as the minimum distance between the cutter and the boundary decreases” in ¶65, as per Fig. 3) as well as on first feedback information from the manipulation terminal (as per “The surgeon's motion commands are provided by measuring the surgeon's guiding force F G. The Cartesian velocity demand for the position controller is set according to the surgeon's force” in ¶63) and second feedback information produced from an external environmental force (as per “Assistance or resistance is achieved by sensing the applied force direction and applying power to the motors in a combination which is such as to produce force either along that force vector for assistance, or backwards along that force vector for resistance” in ¶83, as per “In reality, if a tip force is applied, the surgeon's “control algorithm” would compensate for lowered velocity by applying a higher guiding force, and, when cutting, this change of force is perceived as due to contact with a harder material” in ¶119), compensating drive information applied by the surgical robot to the manipulation terminal so that, when the manipulation terminal moves out of the safe zone, (as per “Instead, the position control gains are set to very high values, with the position demand set to the nearest point on the boundary in order to push the cutter back into the safe region” in ¶66) an impact of the external environmental force on driving of the manipulation terminal is reduced, eliminated or restricted, (as per “This simple change of the boundary control algorithm significantly improves the task of guiding the robot. When near the boundary, the surgeon can move the cutter along or away from the boundary with a very low force. In addition, guiding-force compensation was introduced, which substantially reduces the over-boundary error” in ¶134)
wherein the first feedback information comprises commanded position and posture information for a joint in the manipulation terminal, (as per “Θd and Θd are joint position and velocity demands respectively and are set by the boundary controller. Θd and Θd are actual joint position and velocity respectively (measured with encoders)” in ¶62)
compensating the drive information applied by the surgical robot to the manipulation terminal comprises:
deriving a third torque of the joint through compensating the joint in the manipulation terminal with a corresponding friction feedforward f, (as per “ƒ and g are the joint friction vector (n×1) and the gravity vector (n×1) respectively. τ is the vector (n×1) of joint motor torques.” in ¶100, as per Eqn. 1)
Harris fails to expressly disclose:
wherein the second feedback information comprises an impedance control model of the external environmental force over the joint in the manipulation terminal,
compensating the drive information applied by the surgical robot to the manipulation terminal comprises:
calculating a first torque in Cartesian space using the impedance control model based on a position and posture difference between a current position and posture and a commanded position and posture of the manipulation terminal and a speed difference between a current speed and a commanded speed of the manipulation terminal
converting the first torque into a second torque that the joint is subject to through a transposition of a Jacobian matrix of the joint at a current angle thereof:
and deriving the drive information from the theoretical output torque Fs, the third torque and the second torque;
or
calculating a first force and a first torque thereof in Cartesian space using the impedance control model based on a position and posture difference between a current position and posture and a commanded position and posture of the manipulation terminal and a speed difference between a current speed and a commanded speed of the manipulation terminal;
converting the first force and the first torque thereof into a second force and a second torque thereof that the joint is subject to through a transposition of a Jacobian matrix of the joint at a current angle thereof,
deriving a third force and a third torque of the joint through compensating the joint in the manipulation terminal with a corresponding friction feedforward f; and
deriving the drive information from the theoretical output force and the torque thereof Fs,
the third force and the third torques thereof, and the second force and the second torque thereof.
Bowling discloses of a surgical manipulator, wherein compensating the drive information applied by the surgical robot to the manipulation terminal comprises:
converting the first torque into a second torque that the joint is subject to through a transposition of a Jacobian matrix of the joint at a current angle thereof: (as per “Force transformer module 362 transforms this scalar to force FINST. Force FINST is the vector of forces and torques applied to the virtual rigid body at the origin of coordinate system CMVB to advance the energy applicator 184 at the desired velocity.” In ¶193, as per Eqn. 6 - Jacobian transpose used to convert a scalar command into a force/torque vector (wrench), ¶284-¶288 - Jacobian computed from measured pose/current joint angle, as per Eqn. 14/19)
and deriving the drive information from the theoretical output torque Fs, the third torque and the second torque; (as per “Based on the above data, command dynamics module 544 performs an inverse dynamics calculation for the motion of the links and joints. This inverse dynamics calculation produces, for each active joint, the torque that should be applied to the joint to cause motion of the joint to the commanded joint angle” in ¶278, as per “Force transformer module 362 transforms this scalar to force FINST. Force FINST is the vector of forces and torques applied to the virtual rigid body at the origin of coordinate system CMVB to advance the energy applicator 184 at the desired velocity.” In ¶193, as per “Based on the above inputs, the joint motor controller 126 determines the energization signals that should be applied to the associated motor 101 that cause the motor to drive the joint towards the commanded joint angle. It should be understood that the measured joint angle is used as the representation of the actual joint angle” in ¶282)
deriving the drive information from the theoretical output force and the torque thereof Fs, (as per “Based on the above data, command dynamics module 544 performs an inverse dynamics calculation for the motion of the links and joints. This inverse dynamics calculation produces, for each active joint, the torque that should be applied to the joint to cause motion of the joint to the commanded joint angle” in ¶278, as per “Force transformer module 362 transforms this scalar to force FINST. Force FINST is the vector of forces and torques applied to the virtual rigid body at the origin of coordinate system CMVB to advance the energy applicator 184 at the desired velocity.” In ¶193, as per “Based on the above inputs, the joint motor controller 126 determines the energization signals that should be applied to the associated motor 101 that cause the motor to drive the joint towards the commanded joint angle. It should be understood that the measured joint angle is used as the representation of the actual joint angle” in ¶282)
In this way, Bowling operates to manipulate a surgical instrument and an energy applicator extending from the surgical instrument (¶9). Like Harris and Huang, Bowling is concerned with surgical robotics.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the surgical robot of Harris with the surgical manipulator and the impedance control method of Huang with the surgical manipulator as taught by Bowling to enable another standard means of calculating a torque taking into account a plurality of data to cause motion of the joint to the commanded joint angle (¶278). Such modification also applies an inverse-dynamics feedforward torque and other torque components to the joint controllers - Harris teaches friction/gravity terms; Huang teaches impedance-derived task-space control output mapped to joint space using a Jacobian. It would have been obvious to combine/sum these known torque components to form the final motor drive command.
Harris and Bowling fail to expressly disclose:
wherein the second feedback information comprises an impedance control model of the external environmental force over the joint in the manipulation terminal,
calculating a first torque in Cartesian space using the impedance control model based on a position and posture difference between a current position and posture and a commanded position and posture of the manipulation terminal and a speed difference between a current speed and a commanded speed of the manipulation terminal
calculating a first force and a first torque thereof in Cartesian space using the impedance control model based on a position and posture difference between a current position and posture and a commanded position and posture of the manipulation terminal and a speed difference between a current speed and a commanded speed of the manipulation terminal;
Huang discloses of an impedance control method, comprising:
wherein the second feedback information comprises an impedance control model of the external environmental force over the joint in the manipulation terminal, (as per “Calculating a damping control amount in the task space based on a spring-mass-damper model according to a position deviation between the modified desired trajectory and the actual position, a speed deviation between the desired speed and the actual speed, and the actual interaction force;” in ¶20, as per “Taking into account that the impedance control method is used for a force-controlled robotic arm, which has high nonlinearity, the impedance control method of this embodiment proposes to achieve directional decoupled impedance control while also performing realtime compensation for nonlinear terms such as Coriolis force, centrifugal force, and gravity terms in the joint space or task space” in ¶97)
calculating a first torque in Cartesian space using the impedance control model based on a position and posture difference between a current position and posture and a commanded position and posture of the manipulation terminal and a speed difference between a current speed and a commanded speed of the manipulation terminal (as per “Step S121, calculating the damping control amount in the task space based on the springmass-damper model according to the position deviation between the modified desired trajectory and the actual position of the end, the speed deviation between the desired speed and the actual speed of the end, and the actual interaction force” in ¶85, as per “converting the joint force information from the joint space to the task space, and calculating the acceleration control amount in the task space according to the damping control amount, the desired acceleration of the end, and the converted joint force information of the manipulator” in ¶89, as per “calculating the impedance control torque of the robot arm in the joint space based on the Jacobian matrix according to the acceleration control amount in the task space” in ¶93)
calculating a first force and a first torque thereof in Cartesian space using the impedance control model based on a position and posture difference between a current position and posture and a commanded position and posture of the manipulation terminal and a speed difference between a current speed and a commanded speed of the manipulation terminal; (as per “Step S121, calculating the damping control amount in the task space based on the springmass-damper model according to the position deviation between the modified desired trajectory and the actual position of the end, the speed deviation between the desired speed and the actual speed of the end, and the actual interaction force” in ¶85, as per “converting the joint force information from the joint space to the task space, and calculating the acceleration control amount in the task space according to the damping control amount, the desired acceleration of the end, and the converted joint force information of the manipulator” in ¶89, as per “calculating the impedance control torque of the robot arm in the joint space based on the Jacobian matrix according to the acceleration control amount in the task space” in ¶93)
In this way, Huang operates to improve the control accuracy of the force-controlled robotic arm, but also beneficial for improving the flexibility and safety of the robotic arm (¶43). Like Harris and Bowling, Huang is concerned with robotics.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the surgical robot of Harris and the surgical manipulator of Bowling with the impedance control method of Huang to enable another standard means of implementing a impedance control system to take into account for nonlinearity of a controlled robot arm (¶97).
Claim 1 recites alternative ‘or’ implementations; the applied combination teaches at least the first (torque-based) alternative, which is sufficient to meet the limitation.
As per Claim 8, the combination of Harris, Bowling, and Huang teaches of suggests all limitations of Claim 1. Harris fails to expressly disclose wherein calculating a theoretical output torque comprises:
deriving a commanded angle θ for the joint in the manipulation terminal from commanded position and posture information Xd through inverse kinematics;
calculating a theoretical output torque Fs by using the commanded angle θ as an input to a dynamic calculation;
or
calculating a theoretical output force and a torque thereof comprises:
deriving a commanded angle θ for the joint in the manipulation terminal from commanded position and posture information Xd through inverse kinematics;
calculating a theoretical output force and a torque Fs thereof by using the commanded angle θ as an input to a dynamic calculation.
See Claim 1 for teachings of Bowling. Bowling further discloses wherein calculating a theoretical output torque comprises:
deriving a commanded angle θ for the joint in the manipulation terminal from commanded position and posture information Xd through inverse kinematics; (as per “The commanded pose of coordinate system CMVB is applied to the inverse kinematics module 542 shown in FIG. 13C” in ¶272, as per “Based on the commanded pose and preloaded data, the inverse kinematic module 542 determines the desired joint angle of the joints of the manipulator 50. The preloaded data are data that define the geometry of the links and joints” in ¶272)
calculating a theoretical output torque Fs by using the commanded angle θ as an input to a dynamic calculation; (as per “The desired joint angles generated by the inverse kinematic module are applied to a command dynamics module 544, also a motion control module. Command dynamics module differentiates the sequence of joint angles for each joint… Based on the above data, command dynamics module 544 performs an inverse dynamics calculation for the motion of the links and joints. This inverse dynamics calculation produces, for each active joint, the torque that should be applied to the joint to cause motion of the joint to the commanded joint angle” in ¶277-¶278)
or
calculating a theoretical output force and a torque thereof comprises:
deriving a commanded angle θ for the joint in the manipulation terminal from commanded position and posture information Xd through inverse kinematics; (as per “The commanded pose of coordinate system CMVB is applied to the inverse kinematics module 542 shown in FIG. 13C… Based on the commanded pose and preloaded data, the inverse kinematic module 542 determines the desired joint angle of the joints of the manipulator 50. The preloaded data are data that define the geometry of the links and joints” in ¶272)
calculating a theoretical output force and a torque Fs thereof by using the commanded angle θ as an input to a dynamic calculation. (as per “Based on the above data, command dynamics module 544 performs an inverse dynamics calculation for the motion of the links and joints. This inverse dynamics calculation produces, for each active joint, the torque that should be applied to the joint to cause motion of the joint to the commanded joint angle” in ¶278)
In this way, Bowling operates to manipulate a surgical instrument and an energy applicator extending from the surgical instrument (¶9). Like Harris and Huang, Bowling is concerned with surgical robotics.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the surgical robot of Harris with the surgical manipulator and the impedance control method of Huang with the surgical manipulator as taught by Bowling to enable another standard means of calculating a torque taking into account a plurality of data to cause motion of the joint to the commanded joint angle (¶278).
As per Claim 9, the combination of Harris, Bowling, and Huang teaches of suggests all limitations of Claim 1. Harris fails to expressly disclose wherein an input to the impedance control model is derived using a process comprising the steps of:
calculating a position and posture variation for the joint through admittance control based on an equivalent torque F output from a force sensor under an action of the external environmental force;
calculating the position and posture difference between the current position and posture and the commanded position and posture of the manipulation terminal based on the position and posture variation through forward kinematics; and
taking the position and posture difference as the input to the impedance control model.
See Claim 8 for teachings of Bowling. Bowling further discloses:
calculating a position and posture variation for the joint through admittance control based on an equivalent torque F output from a force sensor under an action of the external environmental force; (as per “Summer 698 produces a weighted sum of these two representations of the external forces and torques, force FEXT. Force FEXT includes a force vector component” in ¶342, as per “Accordingly, the signals output by the end effector force/torque sensor 108 are the signals representative of the forces and torques to which energy applicator 184 is exposed” in ¶149, as per “These commanded pose and commanded velocity data are used by the integrator 386 as the initial conditions for the integrations for the current frame. The integrator 386 converts the velocity from coordinate system MNPL to coordinate system CMVB. This conversion is necessary to employ the velocity as an initial condition in the integrations” in ¶218)
calculating the position and posture difference between the current position and posture and the commanded position and posture of the manipulation terminal based on the position and posture variation through forward kinematics; (as per “Distance Δd is defined to be the negative of the magnitude of the distance the energy applicator 184 has drifted from the path segment. In one implementation, distance Δd is computed by determining the negative of the magnitude of the distance between the actual position and the target position” in ¶192, as per “Based on the measured joint angles and preloaded data, the forward kinematics module 562 determines a representation of the actual pose of the end effector 110, coordinate system EFCT, relative to coordinate system MNPL. The preloaded data are data that define the geometry of the links and joints” in ¶284)
In this way, Bowling operates to manipulate a surgical instrument and an energy applicator extending from the surgical instrument (¶9). Like Harris and Huang, Bowling is concerned with surgical robotics.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the surgical robot of Harris with the surgical manipulator and the impedance control method of Huang with the surgical manipulator as taught by Bowling to enable another standard means of calculating a torque taking into account a plurality of data to cause motion of the joint to the commanded joint angle (¶278).
Harris and Bowling fail to expressly disclose wherein an input to the impedance control model is derived using a process comprising the steps of:
taking the position and posture difference as the input to the impedance control model.
See Claim 8 for teachings of Huang. Huang further discloses wherein an input to the impedance control model is derived using a process comprising the steps of:
taking the position and posture difference as the input to the impedance control model. (as per “Calculating a damping control amount in the task space based on a spring-mass-damper model according to a position deviation between the modified desired trajectory and the actual position, a speed deviation between the desired speed and the actual speed, and the actual interaction force;” in ¶20)
In this way, Huang operates to improve the control accuracy of the force-controlled robotic arm, but also beneficial for improving the flexibility and safety of the robotic arm (¶43). Like Harris and Bowling, Huang is concerned with robotics.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the surgical robot of Harris and the surgical manipulator of Bowling with the impedance control method of Huang to enable another standard means of implementing a impedance control system to take into account for nonlinearity of a controlled robot arm (¶97).
As per Claim 10, the combination of Harris, Bowling, and Huang teaches of suggests all limitations of Claim 1. Harris further discloses wherein the manipulation terminal comprises a robotic arm and/or a manipulator, (as per “In this embodiment the axes of the two rotational joints, that is, the pitch and yaw, and the translational joint, that is the in/out extension, intersect in the centre of the robot 4, thus forming a spherical manipulator” in ¶70) wherein the first feedback information comprises commanded position and posture information for a joint in the robotic arm and/or the manipulator, (as per “Θd and Θd are joint position and velocity demands respectively and are set by the boundary controller. Θd and Θd are actual joint position and velocity respectively (measured with encoders)” in ¶62) and wherein the manipulator is configured to fix a surgical instrument thereto and guide the surgical instrument to perform a surgical operation. (as per “The robot 4 further comprises a grip member 16, in this embodiment a handle, which is coupled to the fourth body member 12 and gripped by a surgeon to move the cutting tool 14, and a force sensor unit 18, in this embodiment a force transducer, for sensing the direction and magnitude of the force applied to the grip member 16 by the surgeon. In use, the surgeon operates the robot 4 by applying a force to the grip member 16. The applied force is measured through the force sensor unit 18, which measured force is used by the control unit to operate the motors 22, 30, 40 to assist or resist the movement of the robot 4 by the surgeon” in ¶73)
As per Claim 12, the combination of Harris, Bowling, and Huang teaches of suggests all limitations of Claim 1. Harris further discloses of a surgical robot (as per Fig. 1), comprising a manipulation terminal (as per Fig. 2), the manipulation terminal comprising a robotic arm and/or a manipulator for guiding a surgical instrument to perform a surgical operation, (as per “the axes of the two rotational joints, that is, the pitch and yaw, and the translational joint, that is the in/out extension, intersect in the centre of the robot 4, thus forming a spherical manipulator” in ¶70) wherein the manipulation terminal is controlled using the control method for a surgical robot (as per “In use, the surgeon operates the robot 4 by applying a force to the grip member 16. The applied force is measured through the force sensor unit 18, which measured force is used by the control unit to operate the motors 22, 30, 40 to assist or resist the movement of the robot 4 by the surgeon” in ¶73) as defined in claim 1.
As per Claim 13, the combination of Harris, Bowling, and Huang teaches of suggests all limitations of Claim 1. Harris further discloses of a surgical robot system, comprising a control device, a navigation device and a manipulation terminal, the navigation device configured to track a current position and posture of the manipulation terminal and feed the position and posture information back to the control device (as per “The boundary controller in the main control loop monitors the Cartesian position X of the cutter relative to the boundary of the safe region. It changes the gains of the position controller, and sets the position demand according to the minimum distance between the cutter and the boundary. The surgeon's motion commands are provided by measuring the surgeon's guiding force F G. The Cartesian velocity demand for the position controller is set according to the surgeon's force” in ¶63) the control device configured to control the manipulation terminal using the control method for a surgical robot as defined in claim 1. (as per “determining the proximity of the tool to the NURBS surface; and controlling the at least one drive unit of the robot by resisting movement of the tool in response to the determined proximity to the NURBS surface” in ¶2)
As per Claim 14, the combination of Harris, Bowling, and Huang teaches of suggests all limitations of Claim 1. Harris further discloses wherein the manipulation terminal comprises a robotic arm and a manipulator for guiding a surgical instrument to perform a surgical operation, (as per “In use, the surgeon operates the robot 4 by applying a force to the grip member 16. The applied force is measured through the force sensor unit 18, which measured force is used by the control unit to operate the motors 22, 30, 40 to assist or resist the movement of the robot 4 by the surgeon” in ¶73) the manipulator having a plurality of degrees of freedom (as per “the axes of the two rotational joints, that is, the pitch and yaw, and the translational joint, that is the in/out extension, intersect in the centre of the robot 4, thus forming a spherical manipulator” in ¶70, as per Fig. 4) wherein the first feedback information comprises commanded position and posture information for a joint in the robotic arm and/or the manipulator. (as per “Θd and Θd are joint position and velocity demands respectively and are set by the boundary controller. Θd and Θd are actual joint position and velocity respectively (measured with encoders)” in ¶62)
As per Claim 15, the combination of Harris, Bowling, and Huang teaches of suggests all limitations of Claim 1. Harris fails to expressly disclose wherein the second torque is taken as a torque compensation for the joint obtained by conversion through multiplying the first torque by the transposition of the Jacobian matrix.
See Claim 1 for teachings of Bowling. Bowling further discloses wherein the second torque is taken as a torque compensation for the joint obtained by conversion through multiplying the first torque by the transposition of the Jacobian matrix. (as per “As mentioned above FEAPP is scalar. Force transformer module 362 transforms this scalar to force FINST. Force FINST is the vector of forces and torques applied to the virtual rigid body at the origin of coordinate system CMVB to advance the energy applicator 184 at the desired velocity. These forces and torques are calculated according to the following equation” in ¶193, as per Eqn. 6, as per “Once FBNDRY is determined, this scalar force is converted to an equivalent set of boundary constraining forces and torques, FB — C, that would need to be applied to the virtual rigid body at the origin of coordinate system CMVB, step 534.” In ¶253, as per Eqn. 11, as per Eqns. 14 & 19)
In this way, Bowling operates to manipulate a surgical instrument and an energy applicator extending from the surgical instrument (¶9). Like Harris and Huang, Bowling is concerned with surgical robotics.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the surgical robot of Harris with the surgical manipulator and the impedance control method of Huang with the surgical manipulator as taught by Bowling to enable another standard means of calculating a torque taking into account a plurality of data to cause motion of the joint to the commanded joint angle (¶278).
As per Claim 16, the combination of Harris, Bowling, and Huang teaches of suggests all limitations of Claim 1. Harris further discloses wherein the friction feedforward is calculated from speed information fed back from the joint in the manipulation terminal. (as per “Θd and Θd are actual joint position and velocity respectively (measured with encoders).” In ¶62, as per “where Θ, Θ and Θ are joint position, velocity and acceleration vectors (n×1) respectively. M is the inertia matrix (n×n) of the robot, which is symmetric and positive definite. h is a vector (n×1) of Coriolis and centrifugal torques—the joint torques caused by motion of other joints. ƒ and g are the joint friction vector (n×1) and the gravity vector (n×1) respectively” in ¶100, as per “It implements a simple PD control algorithm for each joint with gravity, friction and guiding force compensation—Eq. (20). The main control loop is more computationally intensive, since it includes coordinate transformations, force sensor handling and boundary control (see Section 5)” in ¶155, as per Eqn. 20)
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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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/T.R.R./Examiner, Art Unit 3658
/TRUC M DO/Primary Examiner, Art Unit 3658