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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 05 August 2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Objections
Claims 8, 10, 18, and 19 are objected to because of the following informalities:
Regarding claim 8, Applicant claims: “wherein the one or more environmental characteristics comprise at least one of a location of one or more Region of Interests (ROIs) associated with the activity within the environment, one or more obstacles in the environment, one or more workpieces located in the environment, one or more obstacles in the environment, one or more workpieces located in the environment, a specification of the environment, a position or an orientation of each of the plurality of robots in the environment.” The examiner recommends amending this limitation to recite: “wherein the one or more environmental characteristics comprise at least one of a location of one or more Regions of Interestand a position or an orientation of each of the plurality of robots in the environment.”
Claim 18 contains language similar to that of claim 8, and is similarly objected to.
Regarding claim 10, Applicant claims:
“Wherein the mobility parameter comprises at least one of a degree of freedom of the plurality of robots, a type of movement of the plurality of robots, a range of motion and flexibility in each of joints of the plurality of robots, an acceleration and deceleration of the plurality of robots, speed ranges of the robot, or an agility of the plurality of robots….” The examiner recommends amending these limitations to recite: “Wherein the mobility parameter comprises at least one of a degree of freedom of the plurality of robots, a type of movement of the plurality of robots, a range of motion and flexibility in each of joints of the plurality of robots, an acceleration and deceleration capability of the plurality of robots, speed ranges of the robot, or an agility of the plurality of robots….”
Claim 19 contains limitations similar to claim 10 and is similarly objected to.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 8, 10-12, 18, and 19 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 8, Applicant claims: “… a specification of the environment….” The examiner asserts that this limitation renders the claim indefinite, as it is unclear what Applicant intends to claim when they refer to a “specification” of an environment. Specifically, the examiner notes that it is unclear whether the “specification” is a type of the “environment,” (i.e., the “environment” is “specified” as a warehouse, a production floor, etc.), whether the “specification” is a “specified portion” of the environment (i.e., a sub-area), whether the “specification” is a quality of the “environment” (i.e., the operating environment measures 100m x 200m) or whether Applicant intends for the “specification” to mean something else entirely. As such, the examiner asserts that is it impossible to ascertain the metes and bounds of “specification of the environment,” rendering the claim indefinite.
Claim 18 is similar in scope to claim 8, and is similarly rejected. Claim 11 is also rejected by virtue of its dependence on rejected claim 8.
Regarding claim 10, Applicant claims: “…or an agility of the plurality of robots….” The examiner asserts that this limitation renders the claim indefinite, as it is unclear how Applicant intends to quantify an “agility.” Specifically, the examiner does not believe that there is any objective standard for measuring how “agile” something is, meaning that an “agility” is a subjective, and therefore relative, measurement, rendering the claim indefinite.
Claim 19 contains limitations similar to those of claim 10, and is similarly rejected.
Regarding claim 12, Applicant claims: “integrating, by the computer, the selected at least one robot….” The examiner asserts that this limitation renders the claim indefinite, as it is unclear what the “selected at least one robot” is being integrated into. Specifically, the examiner notes that the broadest reasonable interpretation of the limitation as claimed covers situations in which only one robot is selected. Integration – by definition – requires that there be more than one element/device/etc. in the “integration,” as an element cannot integrate (i.e., be combined) with itself. As such, the metes and bounds of the claim are unclear, rendering the claim indefinite.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 20 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
101 Analysis – Step 1
Claim 20 is directed towards a “computer program product for integration of a set of robots to perform an activity, the computer program product comprising a computer-readable storage medium having program instructions embodied therewith…”. Per MPEP 2106.03(II), and the cases cited therein, “[a] claim whose BRI covers both statutory and non-statutory embodiments embraces subject matter that is not eligible for patent protection and therefore is directed towards non-statutory subject matter.” The broadest reasonable interpretation of the claimed “computer-readable storage medium” can encompass non-statutory transitory forms of signal transmission, such as a propagating electrical or electromagnetic signal per se. Therefore, claim 20 is not within one of the four statutory categories (process, machine, manufacture, or composition of matter), rather, it is directed towards signals per se. Hence, claim 20 is not patent eligible.
The examiner notes that this rejection may be overcome by amending claim to recite, for example, “A computer program product for integration of a set of robots to perform an activity, the computer program product comprising a non-transitory computer-readable storage medium having program instructions embodied therewith…” or the like.
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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 8, and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Torii (US 20200282549 A1), hereafter Torii.
Regarding claim 1, Torii discloses a computer-implemented method, comprising:
Obtaining, by a computer, a mobility parameter of each of a plurality of robots (0056, The ability management unit 120 determines the capability of the robot 1 at predetermining timing as of that timing. Specifically, the ability management unit 120 determines the capability indicating the ability that the robot can execute on the basis of the ability of the hardware and software of the robot 1 and the state of the robot 1 at the time of determination. 0070, the help management unit 130 acquires the capability of the robot 2 from the cooperation target robot 2 selected by the robot management unit 140…, 0060, the capability determined by the ability management unit 120 are divided into a plurality of categories such as the mobility, the manipulation, and the knowledge, and more detailed functions and attributes are set for each of the categories.);
Determining, by the computer, a collective mobility of a set of robots from the plurality of robots, wherein the collective mobility of the set of robots is a combination of the mobility parameter of each robot in the set of robots (0064, For example, first, the help management unit 130 compares the ability required for execution of the task that has been determined by the task management unit 110 with the capability of the robot 1 determined by the ability management unit 120. Subsequently, the help management unit 130 determines whether or not the capability of the robot 1 satisfies the ability necessary for execution of the task. Furthermore, in a case where the capability of the robot 1 does not satisfy the ability necessary for execution of the task, the help management unit 130 determines the capability required for the other robot 2 to execute the task, and a help list indicating the ability is generated. 0067, For example, the help list illustrated in FIG. 4 indicates attributes or the like required for the robot 2 for execution of the task in terms of the functions of possible speed of travelling and possible travel distance in the category of mobility. 0070, Moreover, the help management unit 130 compares the generated help list with the capability of the robot 2 selected as the cooperation target, and thereby determines whether or not the capability of the robot 2 satisfies the ability indicated in the help list. Examiner's note: the examiner is interpreting the determination as to whether robot 1 satisfies the capability necessary to perform a task, and the subsequent determination as to whether robot 2 satisfies the capability required to perform the task, as a determination of "collective mobility," as the determination of whether or not the combination of robots 1 and 2 can perform a given task is based off of the capabilities of both robots.);
Determining that the collective mobility of the set of robots satisfies a target mobility threshold (0070, Moreover, the help management unit 130 compares the generated help list with the capability of the robot 2 selected as the cooperation target, and thereby determines whether or not the capability of the robot 2 satisfies the ability indicated in the help list. Specifically, first, the help management unit 130 acquires the capability of the robot 2 from the cooperation target robot 2 selected by the robot management unit 140 as described later. Net, the help management unit 130 compares the generated help list with the acquired capability of the robot 2 to determine whether or not the capability of the robot 2 satisfies the ability indicated in the help list. Examiner's note: the examiner is interpreting the "capability necessary to perform the task" as the "target mobility threshold" as claimed, as the "capability" of robots 1 and 2 must at least meet, if not exceed, the "capability necessary to perform the task" in order to perform the task, i.e., the combined "capability" must meet or exceed the "threshold" of the "capability necessary to perform the task");
Configuring, by the computer, the set of robots to:
Integrate in an environment to perform an activity, wherein the integration is performed based on a determination that the collective mobility of the set of robots satisfies the target mobility threshold, and wherein the target mobility threshold is indicative of a mobility for performing the activity in the environment based on one or more environmental characteristics (0104, If the second robot 2 determines that a help can be provided, a reply indicating that a help can be provided is transmitted from the second robot 2 to the first robot 1 (S119). In the first robot 1 that has received the reply that a help can be provided, the cooperation management unit 150 issues a cooperation instruction to the second robot 2 (S121), and the task is executed by cooperation between the first robot 1 and the second robot 2 (S123). 0061, For example, the highest possible speed of travelling, the lowest possible speed of travelling, the possible travel distance, the level difference that can be stepped over, the travelling direction, and the width that allows travelling are set as functions in the category of mobility); and
Perform, based on the integration of the set of robots, the activity in the environment (0104, If the second robot 2 determines that a help can be provided, a reply indicating that a help can be provided is transmitted from the second robot 2 to the first robot 1 (S119). In the first robot 1 that has received the reply that a help can be provided, the cooperation management unit 150 issues a cooperation instruction to the second robot 2 (S121), and the task is executed by cooperation between the first robot 1 and the second robot 2 (S123).).
Claim 20 is similar in scope to claim 1, and is similarly rejected.
Regarding claim 8, Torii discloses the computer-implemented method of claim 1, and further discloses wherein the one or more environmental characteristics comprise at least one or a location of one or more Region of Interests (ROIs) associated with the activity within the environment, one or more obstacles in the environment, one or more workpieces located in the environment, a specification of the environment, a position or an orientation of each of the plurality of robots in the environment (0077, Furthermore, in a case where the robot management unit 140 can acquire map information and position information of each robot in the map information, the robot management unit 140 may select the robot 2 that cooperates with the robot 1 from among at least one or more robots within a range of travel at the time of execution of the task.).
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.
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.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Torii, and further in view of Jagannath (US 20210053221 A1), hereafter Jagannath.
Regarding claim 2, Torii discloses the computer-implemented method of claim 1, and further discloses wherein a requirement for performing the activity in the environment is the target mobility threshold (0070, Moreover, the help management unit 130 compares the generated help list with the capability of the robot 2 selected as the cooperation target, and thereby determines whether or not the capability of the robot 2 satisfies the ability indicated in the help list. Specifically, first, the help management unit 130 acquires the capability of the robot 2 from the cooperation target robot 2 selected by the robot management unit 140 as described later. Net, the help management unit 130 compares the generated help list with the acquired capability of the robot 2 to determine whether or not the capability of the robot 2 satisfies the ability indicated in the help list.)
Torii fails to disclose, however:
Receiving, by the computer, a user command to perform the activity within the environment;
Generating, by the computer, a virtual representation of the environment based on the one or more environmental characteristics and the received user command; and
Computing, by the computer, a requirement for performing the activity in the environment, wherein requirement is computed based on the generated virtual representation and the received user command.
Jagannath, however, in an analogous field of endeavor, does teach:
Receiving, by the computer, a user command to perform the activity within the environment (0064, The warehouse may include an automated system and robots for performing certain user-defined tasks.);
Generating, by the computer, a virtual representation of the environment based on the one or more environmental characteristics and the received user command (0049, Further at step 310, the task execution device 200 may simulate execution of the at least one current task by employing a plurality of robots based on each of the plurality of sentiment parameters applied to at least one associated factor from the set of factors. The task execution device 200 may determine characteristics of the plurality of robots based on a reward point for an optimized collaboration to implement the task.); and
Computing, by the computer, a requirement for performing the activity in the environment, wherein requirement is computed based on the generated virtual representation and the received user command (0037, The dynamic heterogeneous robot allocation unit 212 may be configured to receive the analyzed pattern and process, which may be optimized in the task optimization unit 210. Further, the dynamic heterogeneous robot allocation unit 212 may map the task to the pattern and process received from the task optimization unit 210. Additionally, the dynamic heterogeneous robot allocation unit 212 may identify a plurality of actions that are required to be performed by the robot. Further, the dynamic heterogeneous robot allocation unit 212 may determine features that are required to be acquired by the robot in order to perform the plurality of actions. It should be noted that parameters of features associated with the robot may be adjusted based on the requirement of the task. For example, based on the requirement, speed of the AGV or number of bins of the AGV may be adjusted.).
Torii and Jagannath are analogous because they are in a similar field of endeavor, e.g., collaborative robotics management systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the task simulation of Jagannath in order to provide a means of better determining what robot should collaborate with the primary robot. The motivation to combine is to allow the combination of robots having the highest likelihood of completing the task to be determined prior to execution of the task.
Claims 3-7 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Torii in view of Jagannath, and further in view of Rana (US 20240160229 A1), hereafter Rana.
Regarding claim 3, the combination of Torii and Jagannath teaches the computer-implemented method of claim 2, and Jagannath further teaches wherein the generation of the virtual representation of the environment comprises:
Obtaining, by the computer, the one or more environmental characteristics using at least one of a set of sensors installed within the environment or prestored environment knowledge (0032, The task and collaboration analysis unit 204 may be configured to receive data from each of the input task processing unit 202, an environmental factors database 218, and the past task and collaboration database 216. 0033, The environmental factors database 218 may deal with one or more local and non-local changes in an environment, which may have potential to affect changes in the robot's collaboration. The external factors may include, but are not limited to, current climate of a given location (for example, climate of a city or a locale), online platform offers, seasonal demand of products, festive sales, consumer sentiment, new product launches, or the like. Additionally, the internal factors may include conveyor belt arrangement, number of Autonomous Ground Vehicles (AGVs), which can move autonomously based on instructions of indoor environment, arrangement of warehouse, limiting factor in flow of execution of goals, area where billing or hand-off to next stage happens, warehouse setup, or the like.);
Determining, by the computer, one or more activity parameters associated with the activity based on predefined activity information, the received user command, and the obtained one or more environmental characteristics (0037, The dynamic heterogeneous robot allocation unit 212 may be configured to receive the analyzed pattern and process, which may be optimized in the task optimization unit 210. Further, the dynamic heterogeneous robot allocation unit 212 may map the task to the pattern and process received from the task optimization unit 210. Additionally, the dynamic heterogeneous robot allocation unit 212 may identify a plurality of actions that are required to be performed by the robot. Further, the dynamic heterogeneous robot allocation unit 212 may determine features that are required to be acquired by the robot in order to perform the plurality of actions. It should be noted that parameters of features associated with the robot may be adjusted based on the requirement of the task. For example, based on the requirement, speed of the AGV or number of bins of the AGV may be adjusted.); and
Generating, by the computer, the virtual representation of the environment based on the obtained one or more environmental characteristics and the determined one or more activity parameters (0043, It should be noted that the data may be extracted from a plurality of data sources, which may include the environmental factors database 218…, 0045, Further at step 304, the task execution device 200 may derive a plurality of factors from the extracted data based on the deep learning network…, 0047, Based on the deep learning network, at step 306, the task execution device 200 may determine a plurality of correlations among the plurality of factors…, 0048, Further at step 308, the task execution device 200 may derive a plurality of sentiment parameters for a set of factors from the plurality of factors based on the plurality of correlations…, 0049, Further at step 310, the task execution device 200 may simulate execution of the at least one current task by employing a plurality of robots based on each of the plurality of sentiment parameters applied to at least one associated factor from the set of factors.).
Torii and Jagannath are analogous because they are in a similar field of endeavor, e.g., collaborative robotics management systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the task simulation of Jagannath in order to provide a means of better determining what robot should collaborate with the primary robot. The motivation to combine is to allow the combination of robots having the highest likelihood of completing the task to be determined prior to execution of the task.
The combination of Torii and Jagannath fails to teach, however, wherein the virtual representation corresponds to a digital representation of the environment comprising a position of one or more obstacles, a position of one or more workpieces, and a position and an orientation of the plurality of robots in the environment.
Rana, however, in an analogous field of endeavor, does teach wherein the virtual representation corresponds to a digital representation of the environment comprising a position of one or more obstacles, a position of one or more workpieces, and a position and an orientation of the plurality of robots in the environment (0068, the method 600 includes determining one or more collision parameters based on the determined one or more situational parameters by using the robot management based AI model. In an exemplary embodiment of the present disclosure, the one or more collision parameters include relative position of each of one or more autonomous robots 110 with respect to each other, free space between each of one or more autonomous robots 110, position, anticipated position and speed of each of the one or more autonomous robots 110, one or more obstacles in vicinity of each of the one or more autonomous robots 110 and the like. 0070, the method 600 includes creating a high-fidelity representation of the one or more autonomous robots 110 in a three-dimensional (3D) space to test, replay dynamic behavior of the one or more autonomous robot or a combination thereof. In an exemplary embodiment of the present disclosure, the created high-fidelity representation of the one or more autonomous robots 110 in the three-dimensional (3D) space corresponds to a virtual simulation environment.).
Torii, Jagannath, and Rana are analogous because they are in a similar field of endeavor, e.g., collaborative robotics management systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the virtual representation of Rana in order to provide a means of more effectively visualizing the robots in the environment. The motivation to combine is to ensure that the simulated robotics are simulated as accurately as possible.
Regarding claim 4, the combination of Torii, Jagannath, and Rana teaches the computer-implemented method of claim 3, and Torii further teaches wherein activities are allocated based on the target mobility threshold and an integration feasibility of the set of robots to perform the activity (0120, Subsequently, in the first robot 1, the help management unit. 130 compares the capability of each of the second robot 2 and the third robot 3 with the generated help list to determine whether or not a help can be provided in each of the second robot 2 and third robots 3 (S317). Furthermore, the robot management unit 140 refers to the similarity or complementarity of capability between the first robot 1 and the second robot 2 and the third robot 3, or an evaluation value and the like of each of the second robot 2 and the third robot 3. As a result, a robot to which a help request is to be transmitted is determined from among the robots that can provide a help (S312).)
Torii fails to teach, however, wherein the method further comprises:
Segmenting the activity into a set of sub-activities based on the generated virtual representation of the environment; and
Allocating, by the computer, a corresponding sub-activity from the segmented set of sub-activities to one or more robots from the set of robots for performing the corresponding sub-activity, wherein the corresponding sub-activity is allocated based on the generated virtual representation of the environment and one or more robotic parameters associated with each of the set of robots.
Jagannath, however, in an analogous field of endeavor, does teach:
Segmenting the activity into a set of sub-activities based on the generated virtual representation of the environment (0049, Further at step 310, the task execution device 200 may simulate execution of the at least one current task by employing a plurality of robots based on each of the plurality of sentiment parameters applied to at least one associated factor from the set of factors. The task execution device 200 may determine characteristics of the plurality of robots based on a reward point for an optimized collaboration to implement the task. 0050, Each of the task may include a plurality of actions. Based on complexity of an action, the action may be considered as a task and may further be divided into sub-actions. The tasks may range from optimizing a warehouse to optimizing specific movements, for example, cutting metal sheets.); and
Allocating, by the computer, a corresponding sub-activity from the segmented set of sub-activities to one or more robots from the set of robots for performing the corresponding sub-activity, wherein the corresponding sub-activity is allocated based on the generated virtual representation of the environment and one or more robotic parameters associated with each of the set of robots (0049, Further at step 310, the task execution device 200 may simulate execution of the at least one current task by employing a plurality of robots based on each of the plurality of sentiment parameters applied to at least one associated factor from the set of factors. The task execution device 200 may determine characteristics of the plurality of robots based on a reward point for an optimized collaboration to implement the task. The optimal collaboration may be selected from the previously computed simulation patterns in the reinforcement learning simulation. Further, the task execution device 200 may map characteristics of the optimal collaboration to the available combination of the plurality of robots. 0050, Each of the task may include a plurality of actions. Based on complexity of an action, the action may be considered as a task and may further be divided into sub-actions … The robot behavior association may be finished and the best possible combination may be deployed for executing the current objectives, tasks, or orders. The sub tasks may be allotted to the robots based on associations and based on tasks that need to be performed by the robots.).
Torii, Jagannath, and Rana are analogous because they are in a similar field of endeavor, e.g., collaborative robotics management systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the task decomposition of Jagannath in order to provide a means of better performing the task as a whole. The motivation to combine is to allow the combination of robots having the highest likelihood of completing the task to be determined prior to execution of the task.
Regarding claim 5, the combination of Torii, Jagannath, and Rana teaches the computer-implemented method of claim 3, and Torii teaches it further comprising:
Obtaining, by the computer, one or more robotic parameters associated with each of the plurality of robots available in the environment from a storage unit (0117, As illustrated in FIG. 10, first, a task to be allocated to the first, robot 1 is determined (S301). Next, the task management unit. 110 extracts functions and ability necessary for execution of the allocated task (S303). In addition, the ability management unit 120 generates a capability list indicating the capability of the first robot 1 as of the current time (S305). 0118, Subsequently, the help management unit 130 compares the function and ability necessary for execution of the task with the capability of the first robot 1, and it is thereby determined whether or not the task can be executed by the first robot 1 alone (S307). If the task can be executed by the first robot 1 alone, the first robot 1 alone executes the task. On the other hand, if the task cannot be executed by the first robot 1 alone, the help management unit 130 generates a help list indicating the ability required for execution of the task (S309). 0119, Next, the robot management unit 140 detects robots (the second robot 2 and the third robot 3) that can cooperate with the first robot 1 via communication or a network (S311). Here, the help management unit 130 requests the second robot 2 and the third robot 3 to transmit capability lists as of the current time (S313). In the second robot 2 and the third robot 3, capability lists each indicating the capability as of the current time are generated (S315), and each of the generated capability lists is transmitted to the first robot 1 (S316). 0120, Subsequently, in the first robot 1, the help management unit. 130 compares the capability of each of the second robot 2 and the third robot 3 with the generated help list to determine whether or not a help can be provided in each of the second robot 2 and third robots 3 (S317).); and
Selecting, by the computer, the set of robots from the plurality of robots qualified for completing the activity based on the obtained one or more robotic parameters of each of the plurality of robots, one or more activity parameters, and the generated virtual representation of the environment, wherein the set of robots comprise a primary robot and one or more secondary robots (0120, Furthermore, the robot management unit 140 refers to the similarity or complementarity of capability between the first robot 1 and the second robot 2 and the third robot 3, or an evaluation value and the like of each of the second robot 2 and the third robot 3. As a result, a robot to which a help request is to be transmitted is determined from among the robots that can provide a help (S312). 0121, Then, the help request is transmitted to the determined robot (second robot 2) (S318). In the second robot 2 that has received the help request, a reply indicating that a help can be provided is transmitted to the first robot 1 (S319). 0121, In the first robot 1 that has received the reply that a help can be provided from the second robot 2, the cooperation management unit 150 issues a cooperation instruction to the second robot 2 (S321), and the task is executed by the cooperation of the first robot 1 and the second robot 2 (S323).).
Torii fails to teach, however, wherein the set of robots is selected based on the generated virtual representation of the environment.
Jagannath, however, in an analogous field of endeavor, does teach wherein the set of robots is selected based on the generated virtual representation of the environment (0037, The dynamic heterogeneous robot allocation unit 212 may be configured to receive the analyzed pattern and process, which may be optimized in the task optimization unit 210. Further, the dynamic heterogeneous robot allocation unit 212 may map the task to the pattern and process received from the task optimization unit 210. Additionally, the dynamic heterogeneous robot allocation unit 212 may identify a plurality of actions that are required to be performed by the robot. Further, the dynamic heterogeneous robot allocation unit 212 may determine features that are required to be acquired by the robot in order to perform the plurality of actions. It should be noted that parameters of features associated with the robot may be adjusted based on the requirement of the task. For example, based on the requirement, speed of the AGV or number of bins of the AGV may be adjusted.)
Torii, Jagannath, and Rana are analogous because they are in a similar field of endeavor, e.g., collaborative robotics management systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the task simulation of Jagannath in order to provide a means of better determining what robot should collaborate with the primary robot. The motivation to combine is to allow the combination of robots having the highest likelihood of completing the task to be determined prior to execution of the task.
Regarding claim 6, the combination of Torii, Jagannath, and Rana teaches the computer-implemented method of claim 5, and Torii further teaches wherein the selection of the set of robots from the plurality of robots comprises:
Selecting, by the computer, the primary robot from the plurality of robots qualified for completing the activity based on the one or more robotic parameters of each of the plurality of robots, the one or more activity parameters, the target mobility threshold, and the generated virtual representation of the environment (0117, a task to be allocated to the first, robot 1 is determined (S301). Next, the task management unit. 110 extracts functions and ability necessary for execution of the allocated task (S303). In addition, the ability management unit 120 generates a capability list indicating the capability of the first robot 1 as of the current time (S305). 0118, Subsequently, the help management unit 130 compares the function and ability necessary for execution of the task with the capability of the first robot 1, and it is thereby determined whether or not the task can be executed by the first robot 1 alone (S307).);
Determining, by the computer, the selected primary robot is incapable of performing the activity in the environment by comparing the one or more robotic parameters of the primary robot with the target mobility threshold (0118, Subsequently, the help management unit 130 compares the function and ability necessary for execution of the task with the capability of the first robot 1, and it is thereby determined whether or not the task can be executed by the first robot 1 alone (S307). If the task can be executed by the first robot 1 alone, the first robot 1 alone executes the task. On the other hand, if the task cannot be executed by the first robot 1 alone, the help management unit 130 generates a help list indicating the ability required for execution of the task (S309).); and
Selecting, by the computer, the one or more secondary robots from the plurality of robots to be integrated with the primary robot based on determining that the selected primary robot is incapable of performing the activity in the environment, wherein the one or more secondary robots are determined by correlating the one or more robotic parameters of each of the plurality of robots, the one or more activity parameters, the target mobility threshold, and integration feasibility of the primary robot and the one or more secondary robots to perform the activity (0120, Subsequently, in the first robot 1, the help management unit. 130 compares the capability of each of the second robot 2 and the third robot 3 with the generated help list to determine whether or not a help can be provided in each of the second robot 2 and third robots 3 (S317). Furthermore, the robot management unit 140 refers to the similarity or complementarity of capability between the first robot 1 and the second robot 2 and the third robot 3, or an evaluation value and the like of each of the second robot 2 and the third robot 3. As a result, a robot to which a help request is to be transmitted is determined from among the robots that can provide a help (S312).).
Torii fails to teach, however, wherein the set of robots is selected based on the generated virtual representation of the environment.
Jagannath, however, in an analogous field of endeavor, does teach wherein the set of robots is selected based on the generated virtual representation of the environment (0037, The dynamic heterogeneous robot allocation unit 212 may be configured to receive the analyzed pattern and process, which may be optimized in the task optimization unit 210. Further, the dynamic heterogeneous robot allocation unit 212 may map the task to the pattern and process received from the task optimization unit 210. Additionally, the dynamic heterogeneous robot allocation unit 212 may identify a plurality of actions that are required to be performed by the robot. Further, the dynamic heterogeneous robot allocation unit 212 may determine features that are required to be acquired by the robot in order to perform the plurality of actions. It should be noted that parameters of features associated with the robot may be adjusted based on the requirement of the task. For example, based on the requirement, speed of the AGV or number of bins of the AGV may be adjusted.)
Torii, Jagannath, and Rana are analogous because they are in a similar field of endeavor, e.g., collaborative robotics management systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the task simulation of Jagannath in order to provide a means of better determining what robot should collaborate with the primary robot. The motivation to combine is to allow the combination of robots having the highest likelihood of completing the task to be determined prior to execution of the task.
Regarding claim 7, the combination of Torii, Jagannath, and Rana teaches the computer-implemented method of claim 6, and Torii further teaches wherein the one or more activity parameters comprise at least one of a priority of the activity, a context of the activity, a category, or a sub-category of the activity (0060-0061, As illustrated in FIG. 3, the capability determined by the ability management unit 120 are divided into a plurality of categories such as the mobility, the manipulation, and the knowledge, and more detailed functions and attributes are set for each of the categories… For example, the highest possible speed of travelling, the lowest possible speed of travelling, the possible travel distance, the level difference that can be stepped over, the travelling direction, and the width that allows travelling are set as functions in the category of mobility, and an attribute is set for each of the functions. In the category of manipulation, the weight that can be lifted, the lowest possible height to be lifted to, the highest possible height to be lifted to, the shape that allows lifting, and the size that allows lifting are set as functions, and an attribute is set for each of the functions. In the category of knowledge, map information (for example, map information of a building in which the robot 1 works) and languages are set as functions, and an attribute is set for each of the functions. 0063, The help management unit 130 generates a help list indicating the ability required for the robot 1 to execute a task.).
Regarding claim 10, the combination of Torii, Jagannath, and Rana teaches the computer-implemented method of claim 6, and Torii further teaches wherein the one or more robotic parameters comprise at least one of the mobility parameter or one or more additional parameters associated with each of the plurality of robots (0060, As illustrated in FIG. 3, the capability determined by the ability management unit 120 are divided into a plurality of categories such as the mobility, the manipulation, and the knowledge, and more detailed functions and attributes are set for each of the categories.), and
Wherein the mobility parameter comprises at least one of a degree of freedom of the plurality of robots, a type of movement of the plurality of robots, a range of motion and flexibility in each of joints of the plurality of robots, an acceleration and deceleration of the plurality of robots, speed ranges of the plurality of robots, or an agility of the plurality of robots (0061, For example, the highest possible speed of travelling, the lowest possible speed of travelling, the possible travel distance, the level difference that can be stepped over, the travelling direction, and the width that allows travelling are set as functions in the category of mobility, and an attribute is set for each of the functions.), and
Wherein the one or more additional parameters comprise at least one of a dimensional specification of the plurality of robots, a number and types of joints of the plurality of robots, a payload capacity of the plurality of robots, one or more spatial constraints of the plurality of robots, an external force handling capability of the plurality of robots, precision and accuracy of each of the plurality of robots for performing the activity, or types of tools attached with the plurality of robots (0061, In the category of manipulation, the weight that can be lifted, the lowest possible height to be lifted to, the highest possible height to be lifted to, the shape that allows lifting, and the size that allows lifting are set as functions, and an attribute is set for each of the functions.).
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Torii, and further in view of Li et al. ("Mobility Fitting using 4D RANSAC"), hereafter Li.
Regarding claim 11, Torii discloses the computer-implemented method of claim 8, but fails to disclose wherein the collective mobility of the set of robots is determined using a 3D curve fitting technique.
Li, however, in an analogous field of endeavor, does teach wherein the collective mobility of the set of robots is determined using a 3D curve fitting technique (Page 81, Col. 1, Paragraph 6 - Col. 2, Paragraph 4, We devise a random sampling consensus method in 4D which fits joints to point trajectories by considering three basic types of joints: hinge, slider, and ball joint (Figure 2). Thus, we randomly select a space-time subset by selecting few random trajectories and a subset of their interval. For each random selection, we compute its best fitting mobility model among the predefined set of joints. Typically, articulated motions are defined by joints connecting part pairs. Thus, our random sampling consensus aims at fitting mobility models to pairs of relative trajectory motions. We represent the trajectory motions using a relative scheme which accounts only for the local transformation as defined by a single joint. See also Table 1 on Page 84, and Fig. 11 on Page 86, which shows the "collective mobility" of an "arm" coupled to a "slider".).
Torii and Li are analogous because they are both reasonably pertinent to solving the problem of determining the movement capabilities of a robotic device. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the trajectory-based movement capability determination of Li in order to provide a means of better determining the collective mobility of a plurality of robots. The motivation to combine is to allow the respective degrees of freedom of constituent robots to be better determined.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Torii, and further in view of Lu (US 20240189996 A1), hereafter Lu.
Regarding claim 12, Torii discloses the computer-implemented method of claim 1, but fails to disclose it further comprising:
Obtaining, by the computer, a set of inputs associated with the set of robots from a set of sensors while the set of robots are performing the activity in the environment;
Determining, by the computer, that the set of robots failed to perform the activity in the environment based on the obtained set of inputs;
Selecting, by the computer, at least one robot from the plurality of robots based on determining that the set of robots failed to perform the activity in the environment, wherein the at least one robot is selected based on the target mobility threshold, one or more robotic parameters, and the one or more environmental characteristics;
Integrating, by the computer, the selected at least one robot; and
Configuring, by the computer, the selected at least one robot to perform the activity in the environment based on integration of the selected at least one robot, wherein the integration of the selected at least one robot is performed based on the target mobility threshold, the collective mobility of the at least one robot, the one or more robotic parameters, and the one or more environmental characteristics.
Lu, however, in an analogous field of endeavor, does teach:
Obtaining, by the computer, a set of inputs associated with the set of robots from a set of sensors while the set of robots are performing the activity in the environment (0089, the machine learning engine 141 may assign a task and/or build a mission based on a result associated with a completed a mission or task. In some cases, based on the result (e.g., a failed result due to image quality of captured images, a failed result due to an incomplete repair of equipment 123, etc.), the server 110 may control a device 105 (e.g., device 105-c, etc.), control a transport instrument, and/or output notifications to an operator (e.g., via device 105-a, etc.) to repeat the mission or task.);
Determining, by the computer, that the set of robots failed to perform the activity in the environment based on the obtained set of inputs (0089, the machine learning engine 141 may assign a task and/or build a mission based on a result associated with a completed a mission or task. In some cases, based on the result (e.g., a failed result due to image quality of captured images, a failed result due to an incomplete repair of equipment 123, etc.), the server 110 may control a device 105 (e.g., device 105-c, etc.), control a transport instrument, and/or output notifications to an operator (e.g., via device 105-a, etc.) to repeat the mission or task.);
Selecting, by the computer, at least one robot from the plurality of robots based on determining that the set of robots failed to perform the activity in the environment, wherein the at least one robot is selected based on the target mobility threshold, one or more robotic parameters, and the one or more environmental characteristics (0090, For example, a failed mission may have been implemented using a robot device (e.g., device 105-c) incapable of flight. The server 110 may repeat the mission (or one or more tasks of the mission) using a robot device (e.g., device 105-e) that is capable of flight. In some other examples, a failed mission may have been implemented using a robot device (e.g., device 105-f) for which a deficiency with respect to payload (e.g., lack of articulated arms or ability to control a tool) resulted in the failed mission. The server 110 may repeat the mission (or one or more tasks of the mission) using a robot device (e.g., device 105-g) having a payload (e.g., articulated arms, a drill, etc.) capable of completing the mission.);
Integrating, by the computer, the selected at least one robot (0090, For example, a failed mission may have been implemented using a robot device (e.g., device 105-c) incapable of flight. The server 110 may repeat the mission (or one or more tasks of the mission) using a robot device (e.g., device 105-e) that is capable of flight. In some other examples, a failed mission may have been implemented using a robot device (e.g., device 105-f) for which a deficiency with respect to payload (e.g., lack of articulated arms or ability to control a tool) resulted in the failed mission. The server 110 may repeat the mission (or one or more tasks of the mission) using a robot device (e.g., device 105-g) having a payload (e.g., articulated arms, a drill, etc.) capable of completing the mission.); and
Configuring, by the computer, the selected at least one robot to perform the activity in the environment based on integration of the selected at least one robot, wherein the integration of the selected at least one robot is performed based on the target mobility threshold, the collective mobility of the at least one robot, the one or more robotic parameters, and the one or more environmental characteristics (0090, For example, a failed mission may have been implemented using a robot device (e.g., device 105-c) incapable of flight. The server 110 may repeat the mission (or one or more tasks of the mission) using a robot device (e.g., device 105-e) that is capable of flight. In some other examples, a failed mission may have been implemented using a robot device (e.g., device 105-f) for which a deficiency with respect to payload (e.g., lack of articulated arms or ability to control a tool) resulted in the failed mission. The server 110 may repeat the mission (or one or more tasks of the mission) using a robot device (e.g., device 105-g) having a payload (e.g., articulated arms, a drill, etc.) capable of completing the mission.).
Torii and Lu are analogous because they are in a similar field of endeavor, e.g., robot management systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the failure recovery of Lu in order to provide a means of ensuring a task is properly performed. The motivation to combine is to ensure that any task that is requested and capable of being carried out, is properly carried out.
Claims 15, 16, 18, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Torii in view of Rana.
Regarding claim 15, Torii discloses a system, comprising:
A processor set (0052, the control device according to the present embodiment may be included in an information processing server or the like connected with the robot via a network) configured to:
Obtain a mobility parameter of a primary robot (0117-0118, As illustrated in FIG. 10, first, a task to be allocated to the first, robot 1 is determined (S301). Next, the task management unit. 110 extracts functions and ability necessary for execution of the allocated task (S303). In addition, the ability management unit 120 generates a capability list indicating the capability of the first robot 1 as of the current time (S305)… Subsequently, the help management unit 130 compares the function and ability necessary for execution of the task with the capability of the first robot 1, and it is thereby determined whether or not the task can be executed by the first robot 1 alone (S307). If the task can be executed by the first robot 1 alone, the first robot 1 alone executes the task. On the other hand, if the task cannot be executed by the first robot 1 alone, the help management unit 130 generates a help list indicating the ability required for execution of the task (S309). 0067, For example, the help list illustrated in FIG. 4 indicates attributes or the like required for the robot 2 for execution of the task in terms of the functions of possible speed of travelling and possible travel distance in the category of mobility.);
Determine a collective mobility of the primary robot and one or more secondary robots from a plurality of robots, wherein the collective mobility parameter of the primary robot and the one or more secondary robots is a combination of the mobility parameter of the primary robot and the mobility parameter of the one or more secondary robots (0120, Subsequently, in the first robot 1, the help management unit. 130 compares the capability of each of the second robot 2 and the third robot 3 with the generated help list to determine whether or not a help can be provided in each of the second robot 2 and third robots 3 (S317). Furthermore, the robot management unit 140 refers to the similarity or complementarity of capability between the first robot 1 and the second robot 2 and the third robot 3, or an evaluation value and the like of each of the second robot 2 and the third robot 3. As a result, a robot to which a help request is to be transmitted is determined from among the robots that can provide a help (S312). 0067, For example, the help list illustrated in FIG. 4 indicates attributes or the like required for the robot 2 for execution of the task in terms of the functions of possible speed of travelling and possible travel distance in the category of mobility. 0070, Moreover, the help management unit 130 compares the generated help list with the capability of the robot 2 selected as the cooperation target, and thereby determines whether or not the capability of the robot 2 satisfies the ability indicated in the help list. Examiner's note: the examiner is interpreting the determination as to whether robot 1 satisfies the capability necessary to perform a task, and the subsequent determination as to whether robot 2 satisfies the capability required to perform the task, as a determination of "collective mobility," as the determination of whether or not the combination of robots 1 and 2 can perform a given task is based off of the capabilities of both robots.);
Determine that the collective mobility of the set of robots satisfies a target mobility threshold (0120, Subsequently, in the first robot 1, the help management unit. 130 compares the capability of each of the second robot 2 and the third robot 3 with the generated help list to determine whether or not a help can be provided in each of the second robot 2 and third robots 3 (S317). Furthermore, the robot management unit 140 refers to the similarity or complementarity of capability between the first robot 1 and the second robot 2 and the third robot 3, or an evaluation value and the like of each of the second robot 2 and the third robot 3. As a result, a robot to which a help request is to be transmitted is determined from among the robots that can provide a help (S312). 0067, For example, the help list illustrated in FIG. 4 indicates attributes or the like required for the robot 2 for execution of the task in terms of the functions of possible speed of travelling and possible travel distance in the category of mobility. Examiner's note: the examiner is interpreting the "capability necessary to perform the task" as the "target mobility threshold" as claimed, as the "capability" of robots 1 and 2 must at least meet, if not exceed, the "capability necessary to perform the task" in order to perform the task, i.e., the combined "capability" must meet or exceed the "threshold" of the "capability necessary to perform the task");
Select the one or more secondary robots to perform an activity based on a determination that the collective mobility of the set of robots satisfies the target mobility threshold, wherein the target mobility threshold is indicative of a mobility for performing the activity in an environment based on one or more environmental characteristics, and wherein the one or more secondary robots are selected for enabling the primary robot to perform the activity in the environment (0121, Then, the help request is transmitted to the determined robot (second robot 2) (S318). In the second robot 2 that has received the help request, a reply indicating that a help can be provided is transmitted to the first robot 1 (S319). In the first robot 1 that has received the reply that a help can be provided from the second robot 2, the cooperation management unit 150 issues a cooperation instruction to the second robot 2 (S321), and the task is executed by the cooperation of the first robot 1 and the second robot 2 (S323).);
Configure the primary robot and the selected one or more secondary robots to:
Integrate in the environment (0121, Then, the help request is transmitted to the determined robot (second robot 2) (S318). In the second robot 2 that has received the help request, a reply indicating that a help can be provided is transmitted to the first robot 1 (S319). In the first robot 1 that has received the reply that a help can be provided from the second robot 2, the cooperation management unit 150 issues a cooperation instruction to the second robot 2 (S321), and the task is executed by the cooperation of the first robot 1 and the second robot 2 (S323).); and
Perform, based on the integration of the primary robot and the one or more secondary robots, the activity in the environment (0121, Then, the help request is transmitted to the determined robot (second robot 2) (S318). In the second robot 2 that has received the help request, a reply indicating that a help can be provided is transmitted to the first robot 1 (S319). In the first robot 1 that has received the reply that a help can be provided from the second robot 2, the cooperation management unit 150 issues a cooperation instruction to the second robot 2 (S321), and the task is executed by the cooperation of the first robot 1 and the second robot 2 (S323).).
Torii fails to explicitly disclose, however, wherein the collective mobility of the primary robot and one or more secondary robots from a plurality of robots is determined using an Artificial Intelligence (AI) model.
Rana, however, in an analogous field of endeavor, does teach wherein combined robotic capabilities are determined using an AI model (0031, The AI based computing system 106 determines one or more robotic capabilities associated with the autonomous robot based on the received set of commands and predefined robotic information. The AI based computing system 106 captures the one or more positional parameters by using the one or more sensors 112. Furthermore, the AI based computing system 106 broadcasts the determined one or more robotic capabilities and the captured one or more positional parameters to each of the one or more autonomous robots 110. The AI based computing system 106 determines one or more situational parameters associated with the one or more autonomous robots 110 based on one or more responses of the broadcasted one or more robotic capabilities and the broadcasted one or more positional parameters, the received set of commands, the determined one or more robotic capabilities and the captured one or more positional parameters by using a robot management based Artificial Intelligence (AI) model.)
Torii and Rana are analogous because they are in a similar field of endeavor, e.g., collaborative robotic management systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the AI model parameter determination of Rana in order to provide a more robust form of robotic capability determination. The motivation to combine is to allow both individual and combined robotic capabilities to be iterated and improved over time.
Regarding claim 16, the combination of Torii and Rana teaches the system of claim 15, and Torii further teaches wherein the processor set is further configured to determine that the obtained mobility parameter of the primary robot failed to satisfy the target mobility threshold (0118, Subsequently, the help management unit 130 compares the function and ability necessary for execution of the task with the capability of the first robot 1, and it is thereby determined whether or not the task can be executed by the first robot 1 alone (S307). If the task can be executed by the first robot 1 alone, the first robot 1 alone executes the task. On the other hand, if the task cannot be executed by the first robot 1 alone, the help management unit 130 generates a help list indicating the ability required for execution of the task (S309). 0060, the capability determined by the ability management unit 120 are divided into a plurality of categories such as the mobility, the manipulation, and the knowledge, and more detailed functions and attributes are set for each of the categories.).
Regarding claim 18, the combination of Torii and Rana teaches the system of claim 15, and Torii further teaches wherein the one or more environmental characteristics comprise at least one of a location of one or more Region of Interests (ROIs) associated with the activity within the environment, one or more obstacles in the environment, one or more workpieces located in the environment, a specification of the environment, a position or an orientation of each of the plurality of robots in the environment (0077, Furthermore, in a case where the robot management unit 140 can acquire map information and position information of each robot in the map information, the robot management unit 140 may select the robot 2 that cooperates with the robot 1 from among at least one or more robots within a range of travel at the time of execution of the task.).
Regarding claim 19, the combination of Torii and Rana teaches the system of claim 15, and Torii further teaches wherein the mobility parameter comprises at least one of a degree of freedom of the set of robots, a type of movement of the set of robots, a range of motion and flexibility in each of joints of the set of robots, an acceleration and deceleration of the set of robots, speed ranges of the set of robots, or an agility of the set of robots (0061, For example, the highest possible speed of travelling, the lowest possible speed of travelling, the possible travel distance, the level difference that can be stepped over, the travelling direction, and the width that allows travelling are set as functions in the category of mobility, and an attribute is set for each of the functions.).
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Torii in view of Rana, and further in view of Jagannath.
Regarding claim 17, the combination of Torii and Rana teaches the system of claim 16, and Torii further teaches wherein, in the selection of the one or more secondary robots, the processor set is further configured to:
Select, based on determining that the obtained mobility parameter of the primary robot failed to satisfy the target mobility threshold, the one or more secondary robots from a plurality of robots to be integrated with the primary robot for performing the activity in the environment (0118, Subsequently, the help management unit 130 compares the function and ability necessary for execution of the task with the capability of the first robot 1, and it is thereby determined whether or not the task can be executed by the first robot 1 alone (S307). If the task can be executed by the first robot 1 alone, the first robot 1 alone executes the task. On the other hand, if the task cannot be executed by the first robot 1 alone, the help management unit 130 generates a help list indicating the ability required for execution of the task (S309).), wherein the one or more secondary robots are selected based on one or more robotic parameters of each of the plurality of robots, one or more activity parameters, the target mobility threshold, and an integration feasibility of the primary robot and the one or more secondary robots to perform the activity (0119, Next, the robot management unit 140 detects robots (the second robot 2 and the third robot 3) that can cooperate with the first robot 1 via communication or a network (S311). Here, the help management unit 130 requests the second robot 2 and the third robot 3 to transmit capability lists as of the current time (S313). In the second robot 2 and the third robot 3, capability lists each indicating the capability as of the current time are generated (S315), and each of the generated capability lists is transmitted to the first robot 1 (S316). 0120, Subsequently, in the first robot 1, the help management unit. 130 compares the capability of each of the second robot 2 and the third robot 3 with the generated help list to determine whether or not a help can be provided in each of the second robot 2 and third robots 3 (S317). Furthermore, the robot management unit 140 refers to the similarity or complementarity of capability between the first robot 1 and the second robot 2 and the third robot 3, or an evaluation value and the like of each of the second robot 2 and the third robot 3. As a result, a robot to which a help request is to be transmitted is determined from among the robots that can provide a help (S312). 0060, the capability determined by the ability management unit 120 are divided into a plurality of categories such as the mobility, the manipulation, and the knowledge, and more detailed functions and attributes are set for each of the categories.).
The combination of Torii and Rana fails to explicitly teach, however, wherein the secondary robot is selected based on a virtual representation of the environment.
Jagannath, however, in an analogous field of endeavor, does teach wherein collaborative robots are chosen based on a simulation of the environment (0049, Further at step 310, the task execution device 200 may simulate execution of the at least one current task by employing a plurality of robots based on each of the plurality of sentiment parameters applied to at least one associated factor from the set of factors. The task execution device 200 may determine characteristics of the plurality of robots based on a reward point for an optimized collaboration to implement the task.)
Torii, Rana, and Jagannath are analogous because they are in a similar field of endeavor, e.g., collaborative robotics management systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the task simulation of Jagannath in order to provide a means of better determining what robot should collaborate with the primary robot. The motivation to combine is to allow the combination of robots having the highest likelihood of completing the task to be determined prior to execution of the task.
Allowable Subject Matter
Claims 9, 13, and 14 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding claim 9, the closest pieces of prior art are Torii, Jagannath, Rana, Li et al., Lu, Skubch (US 20200016754 A1), Krohne (US 20170057081 A1), and Jain (US 20220305646 A1).
Torii teaches a system for collaborative robot task performance, wherein responsive to a determination that a first robot is insufficient to perform a particular task, a second or multiple other robot(s) are identified which would allow the particular task to be performed by collaboration between the first robot and the second or multiple other robots.
Jagannath teaches a method for task execution in a heterogeneous robotic environment, wherein data associated with a plurality of data categories are used to derive a plurality of factors, which are used to determine a plurality of correlations, which are used to determine a plurality of parameters based on a result of a simulation of a current task by a plurality of robots.
Rana teaches an artificial intelligence-based system for managing a heterogeneous swarm of robots, wherein responsive to receiving a command from a user interface, one or more capabilities associated with the plurality of robots are determined, and a task corresponding to the command from the user interface is delegated to one or more of the autonomous robots based on the determined capabilities of each of the plurality of robots.
Li et al. teaches a method for determining the degrees-of-freedom of a robot based on a plurality of trajectories associated with determined points on the robot.
Lu teaches a robotic mission determination system, wherein information associated with a task received from a user is used to determine the optimal robot for performing the task.
Skubch teaches a method for performing execution of a centralized and decentralized control plan, wherein based on received sensor data captured by a plurality of autonomous robots, a determination is made as to the task allocation for each of the autonomous robots, which collaboratively determine a solution based on one or more plan constraints.
Krohne teaches a modularized robot, wherein a plurality of mobile robot bases are operable to couple to a plurality of robotic tool heads in order to perform any one of a plurality of tasks required in an environment.
Jain teaches a system for parameter tuning for a robotic manipulator, wherein based on a task specification, a plurality of physical parameters, and a plurality of control parameters, a simulated robotic manipulator is compared to the state values of a real-world robot, and the parameters of the real-world robot are updated based on an optimization algorithm.
No reference, however, as a whole or in combination, teaches, discloses, suggests, or otherwise renders obvious:
The computer-implemented method of claim 1, wherein the determination of the collective mobility of the set of robots comprises:
Generating, by the computer, a set of point clouds associated with the obtained mobility parameter for each of the set of robots, wherein the mobility parameter corresponds to an ability of each of the set of robots to move and navigate in the environment to perform the activity, and wherein the set of point clouds corresponds to data points representing reachable positions and orientations of the set of robots in the environment;
Determining, by the computer, a set of coupling points associated with each of the set of robots based on the generated set of point clouds;
Merging, by the computer, the generated set of point clouds for each of the set of robots based on the determined set of coupling points; and
Determining the collective mobility of the set of robots based on a result of the merging of the generated set of point clouds.
Regarding claim 13, the closest pieces of prior art are Torii, Jagannath, Rana, Li et al., Lu, Skubch, Krohne, and Jain.
Torii teaches a system for collaborative robot task performance, wherein responsive to a determination that a first robot is insufficient to perform a particular task, a second or multiple other robot(s) are identified which would allow the particular task to be performed by collaboration between the first robot and the second or multiple other robots.
Jagannath teaches a method for task execution in a heterogeneous robotic environment, wherein data associated with a plurality of data categories are used to derive a plurality of factors, which are used to determine a plurality of correlations, which are used to determine a plurality of parameters based on a result of a simulation of a current task by a plurality of robots.
Rana teaches an artificial intelligence-based system for managing a heterogeneous swarm of robots, wherein responsive to receiving a command from a user interface, one or more capabilities associated with the plurality of robots are determined, and a task corresponding to the command from the user interface is delegated to one or more of the autonomous robots based on the determined capabilities of each of the plurality of robots.
Li et al. teaches a method for determining the degrees-of-freedom of a robot based on a plurality of trajectories associated with determined points on the robot.
Lu teaches a robotic mission determination system, wherein information associated with a task received from a user is used to determine the optimal robot for performing the task.
Skubch teaches a method for performing execution of a centralized and decentralized control plan, wherein based on received sensor data captured by a plurality of autonomous robots, a determination is made as to the task allocation for each of the autonomous robots, which collaboratively determine a solution based on one or more plan constraints.
Krohne teaches a modularized robot, wherein a plurality of mobile robot bases are operable to couple to a plurality of robotic tool heads in order to perform any one of a plurality of tasks required in an environment.
Jain teaches a system for parameter tuning for a robotic manipulator, wherein based on a task specification, a plurality of physical parameters, and a plurality of control parameters, a simulated robotic manipulator is compared to the state values of a real-world robot, and the parameters of the real-world robot are updated based on an optimization algorithm.
No reference, however, as a whole or in combination, teaches, discloses, suggests, or otherwise renders obvious:
The computer-implemented method of claim 1, wherein the configuration of robots to integrate comprises:
Validating, by the computer, that stability of the set of robots satisfies a target stability threshold for performing the activity in the environment, wherein the validation is performed using a digital twin simulation technique based on one or more types of forces encountered by the set of robots;
Determining, by the computer, a type of integration to be performed between the set of robots based on the target mobility threshold, the collective mobility of the set of robots and the one or more environmental characteristics, wherein the type of integration is determined based on validating that the stability of the integrated set of robots satisfies the target stability threshold; and
Configuring, by the computer, the set of robots to integrate in the environment for performing the activity based on the type of integration.
Claim 14 similarly contains indicated allowable subject matter due to its dependence on claim 13.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BLAKE A WOOD whose telephone number is (571)272-6830. The examiner can normally be reached M-F, 8:00 AM to 4:30 PM Eastern.
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/BLAKE A WOOD/ Examiner, Art Unit 3658