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 . 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 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.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Response to Amendment/Arguments
The amendments filed on 06/23/2025 have been entered. Claims 1, 3, 5-8, 10, 12-15, 17, and 19-20 remain pending in the application. Examiner notes that the objections, 112 rejections, and 101 rejections have been overcome through the filed amendments, and as such, the examiner has removed those sections.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1, 3, 5-8, 10, 12-15, 17, and 19-20 are rejected under 35 U.S.C. 103 as being obvious over Deits et al. US 20220410378 A1, here referred to as Deits, and in view of Whitman et al., US 20210107150 A1, herein referred to as Whitman.
Regarding claim 1, Deits discloses a legged robot (Fig. 2; system includes a legged robot), acquiring target posture data of the legged robot, wherein the target posture data is posture data corresponding to a target posture to which the legged robot needs to be adjusted (Paragraph 0063; a trajectory target may be a desired pose such as a foot location when contacting a surface), determining plantar force information of the legged robot according to the target posture data, with a friction cone formed between the legged robot and a contact surface in contact with a foot of the legged robot as a constraint condition (Paragraph 0075; contact forces at a contact point between the foot and surface may be determined, a linearized friction cone may be present and acts as a constraint to the forces), controlling the legged robot to be adjusted from a current posture to the target posture according to the plantar force information (Paragraph 0067; actuators may be controlled to allow the robot to execute a planned movement), the plantar force information comprises a plantar force and a plantar force variation (Paragraph 0075; contact force may have minimum and maximum force constraints which can be considered a variability), determining the plantar force of the legged robot according to the target posture data, with the friction cone formed between the legged robot and the contact surface in contact with the foot of the legged robot as the constraint condition (Paragraph 0075; a linearized friction cone may be present and acts as a constraint to the forces, forces are determined based on a planned contact), determining the plantar force variation according to differences between the target posture data and actual posture data (Paragraphs 0075-0076, Fig. 8; forces present are based on the displacement vector from the center of pressure to the center of the contact patch), but fails to disclose the differences comprising a centroid position error and a torso posture error, linearizing a dynamic model and obtaining a linearized dynamic model, according to the centroid position error, the centroid velocity error, the torso posture error, the torso angular velocity error and an initial plantar force variation, constructing a linear quadratic adjustment relationship, with a minimum plantar force variation as an objective and in combination with the linearized dynamic model, and determining the plantar force variation according to the quadratic adjustment relationship.
However, Whitman, in an analogous field of endeavor, teaches a centroid position error, a centroid velocity error, a torso posture error, and a torso angular velocity error (Paragraphs 0049, 0054; variations between a current robot state and an intended robot state may be used for solving the quadratic problem; robot state may include position, orientations, velocities, and angular velocities of the robot center of mass), linearizing a dynamic model and obtaining a linearized dynamic model, according to the centroid position error, the centroid velocity error, the torso posture error, the torso angular velocity error and an initial plantar force variation (Paragraphs 0050, 0058; the solver may linearize the dynamics of the robot, resulting in a linearized robot dynamics solution; an initial state may be fed into the solver based on a current state), constructing a linear quadratic adjustment relationship, with a minimum plantar force variation as an objective and in combination with the linearized dynamic model (Paragraph 0060; solver may use cost functions for optimizing the linearized solution; one of the cost functions can be to minimize contact forces), and determining the plantar force variation according to the quadratic adjustment relationship (Paragraphs 0006, 0060; solution to linearized problem results in contact forces for each leg against a surface).
Therefore, from the teaching of Whitman, it would have been obvious to one of ordinary skill in the art to have modified, with a reasonable expectation for success, the robotic system of Deits to include a centroid position error, a centroid velocity error, a torso posture error, and a torso angular velocity error, linearizing a dynamic model and obtaining a linearized dynamic model, according to the centroid position error, the centroid velocity error, the torso posture error, the torso angular velocity error and an initial plantar force variation, constructing a linear quadratic adjustment relationship, with a minimum plantar force variation as an objective and in combination with the linearized dynamic model, and determining the plantar force variation according to the quadratic adjustment relationship, as taught/suggested by Whitman. The motivation to do so would be to create a model based on variations of actual and targeted states of the robot, and use the model to optimize the robot towards a higher stability state. This can allow the robot to operate in higher stability states over time and can prevent potential falls. Furthermore, the optimization based on a minimization of contact force variance would allow for higher accuracy controls to be utilized as there would be less potential error in the system.
Regarding claim 3, Deits in view of Whitman renders obvious all the limitations of claim 1. Deits further discloses constructing a dynamic model according to the target posture data (Paragraphs 0061, 0063; robot may use a model predictive controller in conjunction with kinematic and inverse dynamic modules; a target trajectory may be used as input into the model predictive controller), but fails to disclose constructing a quadratic optimization relationship, with a minimum plantar force as an optimization objective and in combination with the dynamic model and the constraint condition of the friction cone, and determining the plantar force of the legged robot according to the quadratic optimization relationship. However, Whitman teaches constructing a quadratic optimization relationship, with a minimum plantar force as an optimization objective and in combination with the dynamic model and the constraint condition of the friction cone (Paragraphs 0053, 0060; system solver may optimize the quadratic problem; the solver may include cost terms for optimization such as minimizing contact forces), and determining the plantar force of the legged robot according to the quadratic optimization relationship (Paragraphs 0006, 0060; solution to linearized quadratic problem results in contact forces for each leg against a surface). Therefore, from the teaching of Whitman, it would have been obvious to one of ordinary skill in the art before the effective filing date to have further modified, with a reasonable expectation for success, the robotic system of Deits and Whitman to include constructing a quadratic optimization relationship, with a minimum plantar force as an optimization objective and in combination with the dynamic model and the constraint condition of the friction cone, and determining the plantar force of the legged robot according to the quadratic optimization relationship, as taught/suggested by Whitman. The motivation to do so would be to simplify the model through optimization as this would save computational costs. Additionally, the use of a minimum force as an optimization objective could 1) allow better constraining of the problem for better efficiency, and 2) allow for a more stable solution as a minimization of a force means that there are lower off-center or off-axis forces present that may cause undesired moments or torques.
Regarding claim 5, Deits in view of Whitman renders obvious all the limitations of claim 1. Deits further discloses optimizing the plantar force information according to a linearized dynamic model and obtaining optimized plantar force information, with the friction cone formed between the legged robot and the contact surface in contact with the foot of the legged robot as the constraint condition (Paragraphs 0013, 0075; friction cone for robot leg is linearized and acts as a constraint, retargeted trajectories for robot legs are optimized using centroidal and kinematic equations and result in given forces applied to a contact point), determining a joint torque of each joint of the legged robot according to the optimized plantar force information (Paragraph 0013; optimization can result in associated joint torque vectors), and controlling the legged robot to be adjusted from the current posture to the target posture according to the joint torque (Paragraph 0067; robot controller may use join torque to control the robot to a desired objective or planned touchdown (see desired contact wrenches/patches)).
Regarding claim 6, Deits in view of Whitman renders obvious all the limitations of claim 5. Deits further discloses the plantar force information comprises a plantar force and a plantar force variation (Paragraph 0075; contact force may have minimum and maximum force constraints which can be considered a variability), optimizing the plantar force variation and obtaining an optimized plantar force variation, with a plantar force variation of a current control cycle and a plantar force variation of a previous control cycle as objectives and with the constraint condition of the friction cone and the linearized dynamic model as constraints (Paragraphs 0075; each contact force of each foot may have a friction cone as a constraint with given maximum and minimum forces, each foot contact can be considered a cycle and each planned foot contact can be considered a desired pose/posture of that given foot/leg, a first foot contact may be considered a previous cycle when the robot is determining where to place the next foot), and obtaining the optimized plantar force information according to the optimized plantar force variation and the plantar force (Paragraph 0013; trajectories for robot legs are optimized using centroidal and kinematic equations and result in given forces applied to a contact point).
Regarding claim 7, Deits in view of Whitman renders obvious all the limitations of claim 5. Deits further discloses determining the joint torque of each joint of the legged robot according to the optimized plantar force information and a gravitational torque (Paragraphs 0013, 0067; joint torques may be determined based on a center of mass of the robot and forces occurring at contact points, forces occurring at contact points include minimum and maximum forces which can be considered a variation).
Regarding claim 8, a portion of the claim limitations are similar to those in claim 1 and are rejected using the same rationale as seen above in claim 1. Deits additionally discloses a processor (Fig. 1 item 102; system may include one or more processors), and a memory (Fig. 1 item 104; system may include data storage).
Regarding claims 12-14, the claim limitations are similar to those within claims 5-7, respectively, and are rejected using the same rationale as seen above in claims 5-7.
Regarding claim 10, the claim limitations are similar to those in claim 3 and are rejected using the same rationale as seen above in claim 3.
Regarding claim 17, the claim limitations are similar to those in claim 3 and are rejected using the same rationale as seen above in claim 3.
Regarding claims 15 and 19-20, the claim limitations are similar to those within claims 1 and 5-6, respectively, and are rejected using the same rationale as seen above in claims 1 and 5-6.
Response to Arguments
Applicant's arguments filed on 06/23/2025 have been fully considered but they are not persuasive. Applicant is arguing that the prior art of Whitman fails to teach the feature of “… a minimum plantar force variation as an objective”. However, the primary reference of Deits discloses a plantar force variation, which can effectively be considered a force in general. The obviousness of the claims in view of Whitman lie in the fact that Whitman is teaching a minimization of contact forces, where one of ordinary skill in the art before the effective filing date would realize that a minimization of contact forces would result in the effective minimization of a force variation as well. Furthermore, the minimization of a variance (force or otherwise) is an obvious and well-known way of increasing accuracy of any kinematic system.
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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/C.A.B./Examiner, Art Unit 3658
/JASON HOLLOWAY/Primary Examiner, Art Unit 3658