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 .
This application has been examined. Claims 1-20 are pending.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-4, 6, 11-13, and 18-20, are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Garagic et al. (US 2026/0001224 A1).
As per claims 1, and 11, Garagic et al. disclose a computer-implemented method, and one or more non-transitory computer readable media, for controlling a robot, the method comprising: receiving a task and motion planning (TAMP)-domain language input comprising one or more symbolic elements and one or more continuous elements (see at least [0036] [0045], and [0079-0083], all para. disclose receive the robot task and motion planning comprising a robot in a work space may identify an object that is to be manipulated, one or more manipulable objects and predicate for the object being at a grasped pose); generating a TAMP-domain representation based on the TAMP-domain language input, TAMP-domain language data, and one or more subgraph classification rules (see at least [0102-0106] disclose prediction of contact forces and moments between the robot and its environment. Also, machine learning algorithms are computationally efficient, making them suitable for deployment on edge computational hardware constrained by size, weight, and power); generating a robot plan based on the TAMP-domain representation, a state, and a goal; and causing the robot to perform at least part of the robot plan (see at least [0102-0106] disclose generating a robot plan based on the extract features, detect and semantically classify objects, and analyze dynamic relationships among these features and objects and causing the robot to perform at least part of the robot plan).
As per claims 2, and 12, Garagic et al. disclose the continuous elements comprise at least one of: one or more robot configurations; one or more manipulable objects; one or more placement poses of the one or more manipulable objects; one or more placement surfaces; one or more buttons; or one or more poses at which the one or more buttons can be pressed (see at least [0101-0105] disclose prediction of contact forces and moments between the robot and its environment and object detection, tracking, and identification).
As per claims 3, and 13, Garagic et al. disclose the symbolic elements comprise at least one of: a first predicate for the robot being at a configuration; a second predicate for a gripper of the robot being empty; a third predicate for an object being at a pose; a fourth predicate for the object being at a grasped pose; a fifth predicate for the object being placed on a surface; a sixth predicate for the object being a stick that can be used to press one or more buttons; or a seventh predicate for confirming that the one or more buttons are pressed (see at least [0028] disclose a pose represents the position and orientation and when an object is in the right orientation or pose then the object may be picked up by the robot; and para. [0036] disclose the robot to approach the object from the robot’s current position, the robot may identify a separate object that is in the way).
As per claim 4, Garagic et al. disclose the TAMP-domain language data comprises at least one of one or more types, one or more predicates, one or more constraints, or one or more action schemas (see at least [0103-0106] disclose edge computational hardware constrained by size, weight, and power, and detected objects, obstacles, or potential threats).
As per claim 6, Garagic et al. disclose the one or more action schemas comprise at least one of: a first action schema to move the robot freely from a first configuration to a second configuration along a trajectory; a second action schema to pick an object at a placement pose with a grasp and a third configuration; a third action schema to move the robot from the first configuration to the second configuration while holding the object with the grasp; a fourth action schema to place the object held at the grasp on a surface at the placement pose using the third configuration; a fifth action schema to press a button using a pose and a fourth configuration; or a sixth action schema to press the button using a stick object held at the grasp and the pose and a fifth configuration (see at least [0079-0083] disclose HBPL can be used to select the tasks and stitch the tasks together. When a user instructs a robot to put an object in a location, the actions for the new task plan may be decomposed into: 1) approaching the object, 2) moving in a big arc, 3) avoiding an obstacle and 4) placing the object).
As per claim 18, Garagic et al. disclose generating the TAMP-domain representation comprises serializing one or more constraint graph templates and subgraph tag metadata into a machine-readable format (see at least [0055-0073] disclose the query graph can guide and constrain inference over the probabilistic machine learning model and can result in a tractable inference).
As per claim 19, Garagic et al. disclose the instructions, when executed by the one or more processors, further cause the one or more processors to perform the steps of generating the state based on sensor data (see at least [0055-0056] disclose a task plan is executed, on-part documentation or indicia can be read by sensors of the robot system).
Claim 20, is a system claim corresponding to method claim 1 above. Therefore, it is rejected for the same rationales set forth as above.
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.
Claims 5, 7-10, and 14-17, are rejected under 35 U.S.C. 103 as being unpatentable over Garagic et al. (US 2026/0001224 A1) in view of Gomez Gutierrez et al. (12629833).
As per claim 5, Garagic et al. disclose a constraint to connect a trajectory between a first configuration and a second configuration; a constraint to satisfy a valid grasp pose for an object; a constraint for stable placement of an object on a surface; one or more constraints for a collision-free trajectory (see at least [0101-0106] disclose prediction of contact forces and moments between the robot and its environment. This not only enhances the overall control and stability of the robot but also reduces the overall system cost…. detected objects, obstacles, or potential threats). Garagic et al. do not explicitly disclose inverse kinematics. However, Gomez Gutierrez et al. disclose a constraint for a robot configuration to satisfy inverse kinematics with respect to an object grasped at a first pose and placed at a second pose (see at least columns 14-15, lines 5-53 disclose the path planner 410 may be configured to perform an Inverse Kinematics algorithm that map a desired cartesian pose of the end-effector to a set of joint configurations to obtain the goal configuration). It 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 to modify the teach of Garagic et al. by combining a constraint for a robot configuration to satisfy inverse kinematics with respect to an object grasped at a first pose and placed at a second pose for a trajectory planning of robots.
As per claims 7, and 14, Garagic et al. do not explicitly disclose constraint graph templates. However, Gomez Gutierrez et al. disclose generating the TAMP- domain representation comprises: generating, based on the TAMP-domain language input and the TAMP-domain language data, an abstract syntax tree (AST);generating, based on the AST, one or more constraint graph templates; generating, based on the one or more constraint graph templates and the one or more subgraph classification rules, subgraph tag metadata; and generating, based on the one or more constraint graph templates and the subgraph tag metadata, the TAMP-domain representation (see at least columns 13-14, lines 39-62 disclose the path planner 410 may be configured to output a sequence of collision-free robot configurations or paths to reach one of the assigned goal). It 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 to modify the teach of Garagic et al. by combining a constraint graph templates for a trajectory planning of robots to avoid obstacles.
As per claims 8, and 15, Garagic et al. do not explicitly disclose constraint nodes. However, Gomez Gutierrez et al. disclose the one or more constraint graph templates comprises at least one of: one or more first nodes representing one or more symbolic variables; one or more second nodes representing one or more continuous variables; one or more third nodes representing one or more constraints; one or more cost nodes representing one or more cost functions defined over the one or more continuous variables; or one or more edges to capture one or more dependencies based on the one or more constraints and at least one of the one or more symbolic variables or the one or more continuous variables, wherein each edge included in the one or more edges connects at least one of a symbolic variable included in the one more symbolic variables or a continuous variable included in the one or more continuous variables to at least one of a constraint node included in the one or more third nodes or a cost node included in the one or more cost nodes (see at least columns 13-14, lines 39-62 disclose in traversing the geometric path in obstacle-free scenarios, the initial join configuration starting from rest upon a final joint configuration as initial and final states can be used, while looking for the minimum time). It 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 to modify the teach of Garagic et al. by combining a constraint nodes for a trajectory planning of robots to avoid obstacles.
As per claims 9, and 16, Garagic et al. disclose generating the subgraph tag metadata comprises identifying one or more groups of one or more related constraints and one or more related variables (see at least [0103-0106]).
As per claims 10, and 17, Garagic et al. do not explicitly constraint graph templates. However, Gomez Gutierrez et al. disclose generating the subgraph tag metadata comprises prioritizing at least one of one or more larger subgraphs included in the one or more constraint graph templates or one or more commonly sampled subgraphs included in the one or more constraint graph templates (see at least columns 13-14, lines 39-62 disclose the path planner 410 may be configured to output a sequence of collision-free robot configurations or paths to reach one of the assigned goal). It 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 to modify the teach of Garagic et al. by combining a constraint graph templates for a trajectory planning of robots to avoid obstacles.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure:
. Choi et al. (12443180)
. Miller et al. (US 2024/0289545 A1)
. Raju et al. (US 2024/0029031 A1)
. Kuratani et al. (12290937)
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DALENA TRAN whose telephone number is (571)272-6968. The examiner can normally be reached M-F 7AM-5PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, ADAM MOTT can be reached at 571-270-5376. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/DALENA TRAN/Primary Examiner, Art Unit 3657
Prosecution Insights