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.
Joint Inventors
This application currently names joint inventors. In considering patentability of the claims, the Examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the Examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Response to Amendment/Arguments
The amendments filed on 10/21/2025 have been entered. Claims 1-13 remain pending in the application. Additionally, the claim amendments have overcome the previously presented 35 U.S.C. 101 rejections, and as such, those sections have been removed.
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 1-13 are rejected under 35 U.S.C. 103 as being obvious over Ooba, US 20180085922 A1, herein referred to as Ooba, and in view of Kuffner et al., US 20160023351 A1, herein referred to as Kuffner.
Regarding claim 1, Ooba discloses at least one memory configured to store instructions (Paragraph 0025; system includes memory), acquire skill information which represents one or more skills to be used in a motion planning of a robot (Paragraph 0024; grasp sequencing is determined for a plurality of objects on a conveyor; the sequence itself can be considered skill information wherein the skill is grasping the objects), generate, based on the skill information, a skill tuple which is a set of variables in a system model, the variables being associated with the skill, the system model being set in the motion planning (Paragraphs 0021 and 0031; an index is calculated based on the grasping sequence which includes distancing and rotation between objects; the index can be considered the skill tuple and the distance and rotation can be considered variables for the system and are associated with the grasp sequence skill; the index is integrated into the overall system), generate a skill use operation command that is a temporal logic command representing an operation corresponding to the skill tuple (Paragraph 0036-0037; the robot arm may have controls generated to execute the grasp sequence based on the indexing which is calculated based on the distance and rotation between the objects; a cycle time for execution of the grasp sequence can be determined using the movement speed and the rotation speed required to pick up all the objects in the sequence), controlling the robot based on the skill use operation command (Paragraph 0036-0037; the robot arm may be controlled for a grasp sequence based on an indexing), and a controller (Fig. 4, items 20 and 40, Paragraph 0021; system includes a robot and controller), but fails to explicitly disclose at least one processor, acquiring, from a skill database of skills which are operation-specific modules of a robot, skill information which represents one or more skills to be used in a motion planning of the robot, and the variables including a skill input which represents valid/invalid of each of the one or more skills, the system model being set in the motion planning.
However, Kuffner, in an analogous field of endeavor, teaches at least one processor (Fig. 2A item 202; system includes a processor), acquiring, from a skill database of skills which are operation-specific modules of a robot, skill information which represents one or more skills to be used in a motion planning of the robot (Paragraph 0069; system may include a skill database which associates various information with a given skill to be executed by a robot), and the variables including a skill input which represents valid/invalid of each of the one or more skills, the system model being set in the motion planning (Paragraph 0100; system may include verification of tasks before execution, this can be considered a skill input as the valid/invalid check for each skill is performed prior to robot execution).
Therefore, from the teaching Kuffner, it would have been obvious to one of ordinary skill in the art before the effective filing to have modified, with a reasonable expectation for success, the robotic system of Ooba to include at least one processor, acquiring, from a skill database of skills which are operation-specific modules of a robot, skill information which represents one or more skills to be used in a motion planning of the robot, and the variables including a skill input which represents valid/invalid of each of the one or more skills, the system model being set in the motion planning, as taught/suggested by Kuffner. The motivation to do so would be to utilize a processor (well-known in robotics), as well as implement a database which can track various robotic skills and further implement a validity check on each of the skills. This can allow for better performance as the robot may execute certain skills that are present in the database only in the case that the skill is considered valid for the given operation.
Regarding claim 2, Ooba in view of Kuffner renders obvious all the limitations of claim 1. Ooba further discloses generating a skill use evaluation function that is an evaluation function in which a cost of using the skill is considered (Paragraphs 0035-0036; the robot may measure cycle times for a given grasp sequence; the measurement may be considered the skill use evaluation function and the cycle time may be considered the cost of using the skill) and perform the motion planning through optimization in which the skill use operation command and the skill use evaluation function are used (Paragraph 0038; the robot may optimize the grasp sequence by minimizing cycle times).
Regarding claim 3, Ooba in view of Kuffner renders obvious all the limitations of claim 2. Ooba further discloses the skill information includes information on the cost of using the skill (Paragraphs 0035-0036; a grasp sequence is associated with a measured cycle time), and generating the skill use evaluation function based on the skill information (Paragraphs 0035-0036; the cycle time measurement is performed during the grasp sequence).
Regarding claim 4, Ooba in view of Kuffner renders obvious all the limitations of claim 2. Ooba further discloses generating a control command for the robot based on a target trajectory of a state in the system model, the target trajectory being generated as the motion planning (Paragraphs 0037-0038; control commands may be generated to execute a given grasp sequence; the grasp sequence includes the robot moving to each object for grasping which is a trajectory; the target trajectory state can be one in which the robot has finished the full grasp sequence).
Regarding claim 5, Ooba in view of Kuffner renders obvious all the limitations of claim 1. Ooba further discloses acquiring, as the skill information, information on the skill relating to contact or join between objects or release thereof (Paragraphs 0037-0038; the grasp sequence is one in which the robot grasps objects in a given order).
Regarding claim 6, Ooba in view of Kuffner renders obvious all the limitations of claim 5. Ooba further discloses the skill information includes label information for identifying the skill (Fig. 2 items p1-p6, Paragraphs 0024, 0037; a sequence for grasping includes an order for which objects are grasped; object order numbers p1, p2, etc. may be considered label information and indicate the order for grasping), and acquiring, from a database of the skill information, the skill information associated by the label information with object-to-object relation information, the object-to-object relation information representing a relation between objects in a target state relating to a task of the robot (Paragraphs 0025-0026; the combination calculation unit 12 determines the actual grasp sequencing and stores it in memory; the index calculation unit may determine distancing and rotations between each object which is used for determining the grasp sequence; the distancing and rotation between each object may be considered the object-to-object relation information).
Regarding claim 7, Ooba in view of Kuffner renders obvious all the limitations of claim 1. Ooba further discloses the skill information includes information on: a required time for execution of the skill, an operation command of the skill, a set of states where the skill is executable, and a set of states after execution of the skill (Paragraphs 0037-0038, 0041; a given grasp sequence may have a cycle time which can be the required time to execute; the control of the robot to execute the grasp sequence may be the operation command; the grasping locations needed to execute the grasp sequence may be considered a set of states for skill execution; the robot may continue grasp sequence planning for the next object combination on the conveyor, this can be considered a set of states after execution of the skill), generating the skill use operation command which includes a temporal logic based on the operation command and the required time (Paragraph 0036-0037; the robot arm may have controls generated to execute the grasp sequence based on the indexing which is calculated based on the distance and rotation between the objects; a cycle time for execution of the grasp sequence can be determined using the movement speed and the rotation speed required to pick up all the objects in the sequence), and the temporal logic describing an operation to make a transition of a state in the system model from the set of the states where the skill is executable to the set of states after execution of the skill (Paragraphs 0037-0038; the robot may determine a grasp sequence by leaving out a last object so as to minimize cycle time, where the last object may be associated with a future object combination; this omission of the last object may be considered the temporal logic as it reduces the cycle time of a given grasp sequence and occurs between sets of states (*see above limitation for rationale on state sets)).
Regarding claim 8, Ooba in view of Kuffner renders obvious all the limitations of claim 1. Ooba further discloses the skill tuple at least includes, as the set of variables, a skill input indicative of presence or absence of an input of the skill and a constraint switch variable indicative of presence or absence of a constraint between objects (Paragraphs 0021 and 0031; an index is calculated based on the grasping sequence which includes distancing and rotation between objects; the index can be considered the skill tuple and the distance and rotation can be considered variables for the system and are associated with the grasp sequence skill; the distances and rotation can indicate a presence or absence of a constraint between the objects).
Regarding claim 9, Ooba in view of Kuffner renders obvious all the limitations of claim 4. Ooba further discloses generating one or more state sub-sequences into which a state sequence representing the target trajectory is decomposed, based on a skill input sequence representing presence or absence of an input of the skill in the target trajectory (Paragraphs 0037-0038, 0041; the grasping locations needed to execute the grasp sequence may be considered a set of states for skill execution; movement from one object to another for grasping may be considered a state sub-sequence; the presence or absence of movement for grasping objects can be considered the skill input sequence as the skill (grasping) is only executed when objects are present; no skill input is present when there are no objects to be grasped), configuring one or more controllers of the robot for the respective state sub-sequences (Fig. 4 items 14 and 20, Paragraphs 0037-0038; the robot control unit 14 is used to control the robot 20 to execute the grasp sequence for the objects on the conveyor), and generating the control command into which the controllers are integrated (Fig. 4 items 14 and 20, Paragraphs 0037-0038; the robot is controlled to execute the grasp sequence).
Regarding claim 10, Ooba in view of Kuffner renders obvious all the limitations of claim 9. Ooba further discloses the skill information includes information on a controller to be used for the skill (Fig. 4 items 12 and 20, Paragraph 0024; grasp sequencing is determined for a robot to grasp a plurality of objects on a conveyor; the robot controller and robot are necessarily indicated as the sequence is for grasping objects with the robot), and generating the controllers based on the skill input sequence and the skill information (Fig. 4 items 14 and 20, Paragraph 0024; the robot controller 14 is used to control the robot 20 for executing the grasp sequence; because of this, the robot controller is ‘generated’ as it is generating the necessary control commands for the robot).
Regarding claim 11, the claim limitations are similar to those in claim 1 and are rejected using the same rationale as seen above in claim 1.
Regarding claim 12, the claim limitations are similar to those in claim 1 and are rejected using the same rationale as seen above in claim 1.
Regarding claim 13, the claim limitations are similar to a portion of those in claim 8 and are rejected using the same rationale as seen above in claim 8.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1, 11, and 12 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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
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