DETAILED ACTION
Claims 1-20 are pending.
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 .
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(l) because the character of the lines and text in Figures 1 and 3-6 do not conform to the required standard — every line, number, and letter must be durable, clean, black (except for color drawings), sufficiently dense and dark, and uniformly thick and well-defined. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
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.
Claim(s) 2-3, 9-10 and 16-17 is/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 pre-AIA the applicant regards as the invention.
With regard to claim 2, this claim recites ‘the feasible space volume is determined as an approximation for a current time’ and it is not clear if the feasible space volume is determined as an approximation at current time or if the feasible space volume is determined as an approximation representing/indicating a current time.
With regard to claim 3, this claim recites ‘the feasible space volume is determined as a future time’ and it is not clear how the feasible space volume may be a time.
With regard to claim 9, this claim recites similar limitations to claim 2 and is rejected under the same rationale.
With regard to claim 10, this claim recites similar limitations to claim 3 and is rejected under the same rationale.
With regard to claim 16, this claim recites similar limitations to claim 2 and is rejected under the same rationale.
With regard to claim 17, this claim recites similar limitations to claim 3 and is rejected under the same rationale.
The dependent claims are also rejected under 35 U.S.C. § 112 as they inherit all of the characteristics of the claim from which they depend and none of the dependent claims provide a cure for the indefiniteness of the parent claims.
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(s) 1-7 and 15-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a non-statutory subject matter. The claims do not fall within at least one of the four categories of patent eligible subject matter because the claimed invention is directed to the abstract idea (mental process) of determining a feasible space volume and a control optimization based on the feasible space volume.
Claim 1 recites a computer-implemented method, i.e. a process, which is a statutory category of invention. The claim recites:
determining a feasible space volume based upon, at least in part, the system state and dynamics model;
determining a new control optimization based upon, at least in part, the feasible space volume that may be performed in the human mind, or by a human using a pen and paper. Thus the claim recites an abstract idea (mental processes), see MPEP 2106.04(a).
This judicial exception is not integrated into a practical application because the additional elements, i.e. a computer-implemented method (applying the exception with generic computer technology, see MPEP 2106.04(a)(2) III C), a controller (generally linking the use of the judicial exception to a particular technological environment or field of use, see MPEP 2106.05(h)), obtaining, by a computing device, a system state and dynamics model; obtaining user constraints in a controller for a control optimization; (insignificant extra-solution elements – mere data gathering, see MPEP 2106.05 I A, MPEP 2106.05(g) MPEP 2106.05(d))) and executing a control input for the controller based upon, at least in part, the new control optimization (insignificant extra-solution elements – merely using generic computer technology, see MPEP 2106.05 I A, MPEP 2106.05(g) MPEP 2106.05(d) e.g. receiving or transmitting data over a network) do not impose any meaningful limits on practicing the abstract idea. The claim is therefore directed to an abstract idea.
Note that controllers are well-understood, routine and conventional, see for example Hashimoto et al. U.S. Patent Publication No. 20060279246 [0005] or Hiratsuka et al. U.S. Patent Publication No. 20040010344 [0036, 0065].
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, a computer-implemented method (applying the exception with generic computer technology, see MPEP 2106.04(a)(2) III C), a controller (generally linking the use of the judicial exception to a particular technological environment or field of use, see MPEP 2106.05(h)), obtaining, by a computing device, a system state and dynamics model; obtaining user constraints in a controller for a control optimization; (insignificant extra-solution elements – mere data gathering, see MPEP 2106.05 I A, MPEP 2106.05(g) MPEP 2106.05(d))) and executing a control input for the controller based upon, at least in part, the new control optimization (insignificant extra-solution elements – merely using generic computer technology, see MPEP 2106.05 I A, MPEP 2106.05(g) MPEP 2106.05(d) e.g. receiving or transmitting data over a network) are not considered significantly more. Considering the additionally elements individually and in combination and the claim as a whole, the additional elements do not provide significantly more than the abstract idea. Thus the claim is not patent eligible.
Claim 2 recites ‘the feasible space volume is determined as an approximation for a current time’ (mental process). Thus this claim recites an abstract idea.
Claim 3 recites ‘the feasible space volume is determined as a future time’ (mental process). Thus this claim recites an abstract idea.
Claim 4 recites ‘deriving a new constraint that restricts a rate of change of the feasible space volume’ (mental process). Thus this claim recites an abstract idea.
Claim 5 recites ‘augmenting the user constraints with the new constraint’ (mental process). Thus this claim recites an abstract idea.
Claim 6 recites ‘deriving an update law for parameters in the user constraints such that the feasible space volume is one of increased or decreased within bounds’ (mental process). Thus this claim recites an abstract idea.
Claim 7 recites ‘updating the parameters in the user constraints based upon, at least in part, the update law’ (mental process). Thus this claim recites an abstract idea.
Claim 15 recites a computing system including one or more processors and one or more memories configured to perform operations, i.e. a machine, which is a statutory category of invention. However, the operations performed by the computer system are similar to those recited in claim 1 and are rejected under the same rationale. Note that processors and one or more memories are considered merely applying the exception with generic computer technology – see MPEP 2106.04(a)(2) III C.
Claims 16-17 and 19-20 recite similar limitations to claims 2-3 and 6-7 and are rejected under the same respective rationales.
Claim 18 recites similar limitations to claims 4 and 5 and is rejected under the same rationales as claims 4 and 5.
Claim(s) 8-14 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to a non-statutory subject matter.
Claim 8 is directed to a computer program product residing on a computer readable storage medium having a plurality of instructions stored thereon, i.e. software. “Software per se” is non-statutory under 35 USC 101 because it is merely a set of instructions. See MPEP 2106.03. The examiner suggests considering amending ‘computer readable storage medium’ to ‘non-transitory computer readable storage medium’.
Dependent claims 9-14 are also rejected under 35 U.S.C. § 101 as they inherit all of the characteristics of the claim from which they depend.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-3, 8-10, and 15-17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pack et al. U.S. Patent Publication No. 20090254217 (hereinafter Pack) in view of Takaya et al. U.S. Patent Publication No. 20250249587 (hereinafter Takaya).
Regarding claim 1, Pack teaches computer-implemented method [0009 — a method of controlling a robot includes running multiple applications on a processor, where each application has a robot controller and an action selection engine.] comprising:
obtaining, by a computing device, a system state and dynamics model [0089, Fig. 6 — The action selection engine 200 uses the current state of the robot (e.g. current position, velocity, acceleration, and/or other telemetry of each resource 122) and continuously updates and runs the action selection cycle 210. A feasible sub-region or dynamic window 420 of the action space 410 is computed by the action model 400 based on limits and current state values… A feasible sub-region or dynamic window 420 of the action space 410 is computed by the action model 400 based on limits and current state values];
obtaining constraints in a controller for a control optimization [0080-0081 — [0080 — the commands 440 that correspond to the collaborative best scored outcome 450 are combined together as an overall command 442, which is presented to the robot controller 140 for execution on the robot resources 122 via their corresponding resource control arbiters 122… action models 400 are plug-in components that account for the kinematic and dynamic constraints of all or part of the robot and supports predictions of command outcomes 450 on a local time-horizon. Action models 400 generate possible states that the robot can transition to and create the predicted future outcomes 450. Action models 400 are used or called by the action selection engine 200 to provide feasible commands 440 ];
determining a feasible space based upon, at least in part, the system state and dynamics model [0089, Fig. 6 — A feasible sub-region (feasible space) or dynamic window 420 of the action space 410 is computed by the action model 400 based on limits and current state values];
determining a new control optimization based upon, at least in part, the feasible space [0078 — action selection engine 200 is the coordinating element of the robotics system 100 and runs a fast, optimized action selection cycle 210 (prediction/correction cycle) searching for the best action given the inputs of all the behaviors 300; 0088-0089 — This prediction process is optimized and repeated many times each second (e.g. .about.30 Hz), and works like a predictor-corrector system for the current command set… dynamic window 420 is used to constrain the generated commands 440 so that the action selection engine 200 may select the best available feasible command 440]; and
executing a control input for the controller based upon, at least in part, the new control optimization [0080 — the commands 440 that correspond to the collaborative best scored outcome 450 are combined together as an overall command 442, which is presented to the robot controller 140 for execution on the robot resources 122 via their corresponding resource control arbiters 122].
But Pack fails to clearly specify user constraints and a feasible space volume.
However, Takaya teaches user constraints [0044 — input unit 201, for example, may receive a position of an obstacle during movement of the target object M from the movement source to the movement destination from the user as a constraint condition] and a feasible space volume [0082-0084, Fig. 14 — feasible space volumes are defined using x, y, and z axes].
Pack and Takaya are analogous art. They relate to robot control systems.
Therefore at the time the invention was made, it would have been obvious to a person of ordinary skill in the art to modify the above method, as taught by Pack, by incorporating the above limitations, as taught by Takaya.
One of ordinary skill in the art would have been motivated to do this modification in order to enable a user to provide appropriate constraints, as suggested by Takaya [0044] and to facilitate control in more than 2 dimensions, see Pack [0100].
Regarding claim 2, the combination of Pack and Cotton Takaya all the limitations of the base claims as outlined above.
Further, Pack teaches the feasible space is determined as an approximation for a current time [0079 — action selection engine 200 uses the action models 400 to provide a pool of feasible commands 440 (within physical actuator limits like position, velocity and acceleration) and corresponding outcomes 450 predicted to a time horizon in the future; 0085 – action selection engine 200 uses the action model 400 to predict the expected outcomes 450 of all feasible commands 440 several seconds into the future (approximately the current time)].
Further, Takaya teaches a feasible space volume [0082-0084, Fig. 14 — feasible space volumes are defined using x, y, and z axes].
Regarding claim 3, the combination of Pack and Takaya teaches all the limitations of the base claims as outlined above.
Further, Pack teaches the feasible space is determined as a future time [0079 — action selection engine 200 uses the action models 400 to provide a pool of feasible commands 440 (within physical actuator limits like position, velocity and acceleration) and corresponding outcomes 450 predicted to a time horizon in the future; 0085 – action selection engine 200 uses the action model 400 to predict the expected outcomes 450 of all feasible commands 440 several seconds into the future].
Further, Takaya teaches a feasible space volume [0082-0084, Fig. 14 — feasible space volumes are defined using x, y, and z axes].
Regarding claim 8, Pack teaches a computer program product which, when executed across one or more processors, causes at least a portion of the one or more processors [0009 — a method of controlling a robot includes running multiple applications on a processor, where each application has a robot controller and an action selection engine; 0059-0068 — the robot controllers 140 can publish commands 440 to shared memory of the pub/sub system on the local network 110 that is accessed by control arbiters 120 to pull the commands 440 in any particular order… A server program (the Publish/Subscribe Registry Server) is responsible for creating and initializing the shared memory… robot controller 140 itemized in the robot controller list 154 has a corresponding robot controller memory block 142 in the shared memory of the local network 110. Similarly, every control arbiter 120 itemized in the control arbiter list 156 has a corresponding control arbiter memory block 124 in the shared memory of the local network 110] to perform operations comprising:
obtaining, by a computing device, a system state and dynamics model [0089, Fig. 6 — The action selection engine 200 uses the current state of the robot (e.g. current position, velocity, acceleration, and/or other telemetry of each resource 122) and continuously updates and runs the action selection cycle 210. A feasible sub-region or dynamic window 420 of the action space 410 is computed by the action model 400 based on limits and current state values… A feasible sub-region or dynamic window 420 of the action space 410 is computed by the action model 400 based on limits and current state values];
obtaining constraints in a controller for a control optimization [0080-0081 —the commands 440 that correspond to the collaborative best scored outcome 450 are combined together as an overall command 442, which is presented to the robot controller 140 for execution on the robot resources 122 via their corresponding resource control arbiters 122… action models 400 are plug-in components that account for the kinematic and dynamic constraints of all or part of the robot and supports predictions of command outcomes 450 on a local time-horizon. Action models 400 generate possible states that the robot can transition to and create the predicted future outcomes 450. Action models 400 are used or called by the action selection engine 200 to provide feasible commands 440 ];
determining a feasible space based upon, at least in part, the system state and dynamics model [0089, Fig. 6 — A feasible sub-region (feasible space) or dynamic window 420 of the action space 410 is computed by the action model 400 based on limits and current state values];
determining a new control optimization based upon, at least in part, the feasible space [0078 — action selection engine 200 is the coordinating element of the robotics system 100 and runs a fast, optimized action selection cycle 210 (prediction/correction cycle) searching for the best action given the inputs of all the behaviors 300; 0088-0089 — This prediction process is optimized and repeated many times each second (e.g. .about.30 Hz), and works like a predictor-corrector system for the current command set… dynamic window 420 is used to constrain the generated commands 440 so that the action selection engine 200 may select the best available feasible command 440]; and
executing a control input for the controller based upon, at least in part, the new control optimization [0080 — the commands 440 that correspond to the collaborative best scored outcome 450 are combined together as an overall command 442, which is presented to the robot controller 140 for execution on the robot resources 122 via their corresponding resource control arbiters 122].
But Pack fails to clearly specify a computer program product residing on a computer readable storage medium having a plurality of instructions stored thereon, user constraints and a feasible space volume.
However, Takaya teaches a computer program product residing on a computer readable storage medium having a plurality of instructions stored thereon [0108-0109, Fig. 21, claim 1 — computer 5 includes a central processing unit (CPU) 6, a main memory 7, a storage 8, and an interface 9. For example, each of the above-described robot system 1, the control device 2, the input unit 201, the generation unit 202, the control unit 203, the robot 40, the image device 50, and other control devices is installed in the computer 5. Also, the operation of each processing unit described above is stored in the storage 8 in the form of a program. The CPU 6 reads the program from the storage 8, loads the program into the main memory 7, and executes the above-described process in accordance with the program], user constraints [0044 — input unit 201, for example, may receive a position of an obstacle during movement of the target object M from the movement source to the movement destination from the user as a constraint condition] and a feasible space volume [0082-0084, Fig. 14 — feasible space volumes are defined using x, y, and z axes].
Pack and Takaya are analogous art. They relate to robot control systems.
Therefore at the time the invention was made, it would have been obvious to a person of ordinary skill in the art to modify the above system, as taught by Pack, by incorporating the above limitations, as taught by Takaya.
One of ordinary skill in the art would have been motivated to do this modification in order to facilitate precise program/computer control when required by a user, in order to enable a user to provide appropriate constraints, as suggested by Takaya [0044] and to facilitate control in more than 2 dimensions, see Pack [0100].
Regarding claim 9, the combination of Pack and Takaya teaches all the limitations of the base claims as outlined above and this claim is otherwise rejected under the same rationale as claim 2.
Regarding claim 10, the combination of Pack and Takaya teaches all the limitations of the base claims as outlined above and this claim is otherwise rejected under the same rationale as claim 3.
Regarding claim 15, Pack teaches a computing system including one or more processors and one or more memories [0009 — a method of controlling a robot includes running multiple applications on a processor, where each application has a robot controller and an action selection engine; 0059-0068 — the robot controllers 140 can publish commands 440 to shared memory of the pub/sub system on the local network 110 that is accessed by control arbiters 120 to pull the commands 440 in any particular order] configured to perform operations comprising:
obtaining, by a computing device, a system state and dynamics model [0089, Fig. 6 — The action selection engine 200 uses the current state of the robot (e.g. current position, velocity, acceleration, and/or other telemetry of each resource 122) and continuously updates and runs the action selection cycle 210. A feasible sub-region or dynamic window 420 of the action space 410 is computed by the action model 400 based on limits and current state values… A feasible sub-region or dynamic window 420 of the action space 410 is computed by the action model 400 based on limits and current state values];
obtaining constraints in a controller for a control optimization [0080-0081 —the commands 440 that correspond to the collaborative best scored outcome 450 are combined together as an overall command 442, which is presented to the robot controller 140 for execution on the robot resources 122 via their corresponding resource control arbiters 122… action models 400 are plug-in components that account for the kinematic and dynamic constraints of all or part of the robot and supports predictions of command outcomes 450 on a local time-horizon. Action models 400 generate possible states that the robot can transition to and create the predicted future outcomes 450. Action models 400 are used or called by the action selection engine 200 to provide feasible commands 440 ];
determining a feasible space based upon, at least in part, the system state and dynamics model [0089, Fig. 6 — A feasible sub-region (feasible space) or dynamic window 420 of the action space 410 is computed by the action model 400 based on limits and current state values];
determining a new control optimization based upon, at least in part, the feasible space [0078 — action selection engine 200 is the coordinating element of the robotics system 100 and runs a fast, optimized action selection cycle 210 (prediction/correction cycle) searching for the best action given the inputs of all the behaviors 300; 0088-0089 — This prediction process is optimized and repeated many times each second (e.g. .about.30 Hz), and works like a predictor-corrector system for the current command set… dynamic window 420 is used to constrain the generated commands 440 so that the action selection engine 200 may select the best available feasible command 440]; and
executing a control input for the controller based upon, at least in part, the new control optimization [0080 — the commands 440 that correspond to the collaborative best scored outcome 450 are combined together as an overall command 442, which is presented to the robot controller 140 for execution on the robot resources 122 via their corresponding resource control arbiters 122].
But Pack fails to clearly specify user constraints and a feasible space volume.
However, Takaya teaches user constraints [0044 — input unit 201, for example, may receive a position of an obstacle during movement of the target object M from the movement source to the movement destination from the user as a constraint condition] and a feasible space volume [0082-0084, Fig. 14 — feasible space volumes are defined using x, y, and z axes].
Pack and Takaya are analogous art. They relate to robot control systems.
Therefore at the time the invention was made, it would have been obvious to a person of ordinary skill in the art to modify the above system, as taught by Pack, by incorporating the above limitations, as taught by Takaya.
One of ordinary skill in the art would have been motivated to do this modification in order to enable a user to provide appropriate constraints, as suggested by Takaya [0044] and to facilitate control in more than 2 dimensions, see Pack [0100].
Regarding claim 16, the combination of Pack and Takaya teaches all the limitations of the base claims as outlined above and this claim is otherwise rejected under the same rationale as claim 2.
Regarding claim 17, the combination of Pack and Takaya teaches all the limitations of the base claims as outlined above and this claim is otherwise rejected under the same rationale as claim 3.
Citation of Pertinent Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Kassmann et al. U.S. Patent No. 6381505 that discloses a model predictive control system that determines a feasible control region.
Note that any citations to specific, pages, columns, lines, or figures in the prior art references and any interpretation of the reference should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. See MPEP 2123.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BERNARD G. LINDSAY whose telephone number is (571)270-0665. The examiner can normally be reached Monday through Friday from 8:30 AM to 5:30 PM EST.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Mohammad Ali can be reached on (571)272-4105. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/BERNARD G LINDSAY/
Primary Examiner, Art Unit 2119