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 .
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.
Claims 1-9, 11-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
According to step 1:
claims 1-9 are directed to a system for constraint management.
claims 11-15 are directed to a computer implemented method for constraint management.
According to step 2A, prong 1 the claimed invention is directed to a judicial exception (i.e., an abstract idea).
That is independent claim 1 is generally directed constraint management.
As an example, independent claim 1 recites:
a memory storing one or more instructions; and
a processor executing one or more of the instructions stored on the memory to perform:
determining a context associated with a current task; and
calculating one or more constraints associated with the current task based on the context and a set of constraints.
Then independent claim 11 also generally directed constraint management.
As an example, independent claim 11 recites:
determining a context associated with a current task; and
calculating one or more constraints associated with the current task based on the context and a set of constraints.
That is the limitations,
“a memory storing one or more instructions”; and
“a processor executing one or more of the instructions stored on the memory to perform”:
“determining a context associated with a current task”; and
“calculating one or more constraints associated with the current task based on the context and a set of constraints”
are directed to data recognition, collection of new data, and using the data to perform mathematical calculations.
According to step 2A, prong 2 the judicial exception is not integrated into a practical application. The claims have additional elements of a memory, controller, and battery, sensor, etc. These elements simply apply the judicial exception to a particular technological environment by generally collected data from sensors and performing a mathematical operation within the internals of a processor. The additional elements do not control or implement any system or method outside of the internal of the processor into any practical application. Accordingly, these additional elements do not integrate the abstract into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims can generally read on anything. The claim limitations give rise to the risk over the pre-emption of all applications of an idea because the claims are directed to an abstract and not to the implementation of a specific system or method for controlling operations of anything.
According to step 2B, the claim(s) do not include additional elements that are sufficient to amount to significantly more than the judicial exception because even though the claims recite a general computer, sensor, controller, etc they are merely used to describe data recognition, collection, and mathematical operations using rules to identify options as opposed to implementing a practical application.
Accordingly, the claims recite additional elements that do not amount to significantly more than the judicial exception because the additional element generally links the use of the judicial exception to calculating constraints.- see MPEP 2106.05(h).
Applicant may overcome the 101 rejection by reciting a computer or controller that " a robot and actuator implementing a current task, ………”
The rejection applies to all claims since the rest of the limitations in the claims are rejected for having similar deficiencies as claim 1.
Claim Rejections - 35 USC § 102
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 (i.e., changing from AIA to pre-AIA ) 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 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.
Claim(s) 1-20 are rejected under 35 U.S.C. 102(a)1 as being anticipated by
Regarding claim 1 D'Amelio; Peter (US 2024/0157561 A1) discloses a system for constraint management (manages constraints of position, location, trajectory, proximity, force, acceleration velocity for effectively picking, placing, gripping, moving objects, parcels, etc; sec 0021, 0023, 0026, 0036, 0039, 0040 ) comprising:
a memory storing one or more instructions (sec 0026, 0027, 0033-0037, 0264); and
a processor executing one or more of the instructions stored on the memory (sec 0026, 0027, 0033-0037) to perform:
determining a context associated with a current task (figs. 1-3; context associated with the task of picking and placing; sec 0021, 0023, 0026, 0029-0037); and
calculating one or more constraints associated with the current task based on the context and a set of constraints (calculating constraints of position, location, trajectory, proximity, force, acceleration velocity for effectively picking, placing, gripping, moving objects, parcels, etc based on the context and a set of constraints; sec 0021, 0023, 0026, 0029-0040).
Regarding claim 2 D'Amelio; Peter (US 2024/0157561 A1) discloses the system for constraint management of claim 1, comprising a sensor sensing an aspect of a physical environment (sec 0021, 0022, 0023, 0026, 0029-0040), wherein the processor determines the context associated with the current task based on the aspect of the physical environment (sec 0021, 0022, 0023, 0026, 0029-0040).
Regarding claim 3 D'Amelio; Peter (US 2024/0157561 A1) discloses the system for constraint management of claim 2, wherein the sensor is an image capture device, a force sensor, an acceleration sensor, a pressure sensor, or a proximity sensor (sec 0022, 0026, 0029).
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Regarding claim 4 D'Amelio; Peter (US 2024/0157561 A1) discloses the system for constraint management of claim 1, wherein the current task is a sub-task of one or more sub-tasks for a long-horizon task (long-horizon such as reaching, extending, etc; sec 0021, 0022, 0023, 0026, 0029-0040).
Regarding claim 5 D'Amelio; Peter (US 2024/0157561 A1) discloses the system for constraint management of claim 1, wherein the context is a type of task associated with the current task (sec 0021, 0022, 0023, 0026, 0029-0040).
Regarding claim 6 D'Amelio; Peter (US 2024/0157561 A1) discloses the system for constraint management of claim 1, wherein a constraint of the one or more constraints is a force constraint, an interaction force constraint, a velocity constraint, an acceleration constraint, a proximity constraint, a positional constraint, or a trajectory constraint (constraints of position, location, trajectory, proximity, force, acceleration velocity for effectively picking, placing, gripping, moving objects, parcels, etc; sec 0021, 0023, 0026, 0036, 0039, 0040 ).
Regarding claim 7 D'Amelio; Peter (US 2024/0157561 A1) discloses the system for constraint management of claim 1, comprising a sensor sensing feedback from a human, wherein the processor determines one or more additional constraints associated with the current task based on the feedback from the human (sec 0023, 0041, 0257).
Regarding claim 8 D'Amelio; Peter (US 2024/0157561 A1) discloses the system for constraint management of claim 7, wherein the sensor is an input device, a microphone, a keyboard, or a touchscreen (0028, 0023, 0041, 0257, 0272).
Regarding claim 9 D'Amelio; Peter (US 2024/0157561 A1) discloses the system for constraint management of claim 7, wherein the processor determines the one or more additional constraints associated with the current task based on a large language model (LLM; sec 0325).
Regarding claim 10 D'Amelio; Peter (US 2024/0157561 A1) discloses the system for constraint management of claim 1, comprising:
a robot appendage and an actuator implementing the current task in accordance with the one or more constraints (sec 0036-0040).
Regarding claim 11 D'Amelio; Peter (US 2024/0157561 A1) discloses a computer-implemented method for constraint management (manages constraints of position, location, trajectory, proximity, force, acceleration velocity for effectively picking, placing, gripping, moving objects, parcels, etc; sec 0021, 0023, 0026, 0036, 0039, 0040), comprising:
determining a context associated with a current task (figs. 1-3; context associated with the task of picking and placing; sec 0021, 0023, 0026, 0029-0037); and
calculating one or more constraints associated with the current task based on the context and a set of constraints (calculating constraints of position, location, trajectory, proximity, force, acceleration velocity for effectively picking, placing, gripping, moving objects, parcels, etc based on the context and a set of constraints; sec 0021, 0023, 0026, 0029-0040).
Regarding claim 12 D'Amelio; Peter (US 2024/0157561 A1) discloses the computer-implemented method for constraint management of claim 11, comprising:
sensing an aspect of a physical environment using a sensor (sec 0021, 0022, 0023, 0026, 0029-0040); and
determining the context associated with the current task based on the aspect of the physical environment (sec 0021, 0022, 0023, 0026, 0029-0040).
Regarding claim 13 D'Amelio; Peter (US 2024/0157561 A1) discloses the computer-implemented method for constraint management of claim 12, wherein the sensor is an image capture device, a force sensor, an acceleration sensor, a pressure sensor, or a proximity sensor (sec 0022, 0026, 0029).
Regarding claim 14 D'Amelio; Peter (US 2024/0157561 A1) discloses the computer-implemented method for constraint management of claim 11, wherein the current task is a sub-task of one or more sub-tasks for a long-horizon task (long-horizon such as reaching, extending, etc; sec 0021, 0022, 0023, 0026, 0029-0040).
Regarding claim 15 D'Amelio; Peter (US 2024/0157561 A1) discloses the computer-implemented method for constraint management of claim 11, wherein the context is a type of task associated with the current task (sec 0021, 0022, 0023, 0026, 0029-0040).
Regarding claim 16 D'Amelio; Peter (US 2024/0157561 A1) discloses a constraint efficient robot (robot manages constraints of position, location, trajectory, proximity, force, acceleration velocity for effectively picking, placing, gripping, moving objects, parcels, etc; sec 0021, 0023, 0026, 0036, 0039, 0040 ), comprising:
a memory storing one or more instructions (sec 0026, 0027, 0033-0037, 0264);
a processor executing one or more of the instructions stored on the memory (sec 0026, 0027, 0033-0037) to perform:
determining a context associated with a current task (figs. 1-3; context associated with the task of picking and placing; sec 0021, 0023, 0026, 0029-0037); and
calculating one or more constraints associated with the current task based on the context and a set of constraints (calculating constraints of position, location, trajectory, proximity, force, acceleration velocity for effectively picking, placing, gripping, moving objects, parcels, etc based on the context and a set of constraints; sec 0021, 0023, 0026, 0029-0040); and
a robot appendage and an actuator implementing the current task in accordance with the one or more constraints (sec 0036-0040).
Regarding claim 17 D'Amelio; Peter (US 2024/0157561 A1) discloses the constraint efficient robot of claim 16, comprising a sensor sensing an aspect of a physical environment (sec 0021, 0022, 0023, 0026, 0029-0040),
wherein the processor determines the context associated with the current task based on the aspect of the physical environment (sec 0021, 0022, 0023, 0026, 0029-0040).
Regarding claim 18 D'Amelio; Peter (US 2024/0157561 A1) discloses the constraint efficient robot of claim 17, wherein the sensor is an image capture device, a force sensor, an acceleration sensor, a pressure sensor, or a proximity sensor (sec 0022, 0026, 0029).
Regarding claim 19 D'Amelio; Peter (US 2024/0157561 A1) discloses the constraint efficient robot of claim 16, wherein the current task is a sub-task of one or more sub-tasks for a long-horizon task (long-horizon such as reaching, extending, etc; sec 0021, 0022, 0023, 0026, 0029-0040).
Regarding claim 20 D'Amelio; Peter (US 2024/0157561 A1) discloses the constraint efficient robot of claim 16, wherein the context is a type of task associated with the current task (sec 0021, 0022, 0023, 0026, 0029-0040).
Conclusion
The prior art (US 20250068966 A1; US 20250042032 A1) made of record and not relied upon is considered pertinent to applicant's disclosure.
Communication
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RONNIE MANCHO whose telephone number is (571)272-6984. The examiner can normally be reached Mon-Thurs.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Adam Mott can be reached at 571 270 5376. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RONNIE M MANCHO/Primary Examiner, Art Unit 3657
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