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 .
Claim Objections
Claim 1 is objected to because of the following informalities:
In claim 1, “a state history of the environmental agent to a reference trajectory” should be “a state history [[of]] associated with the environmental agent instance identifier to a reference trajectory”
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claim 1 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of U.S. Patent No. US 12296849 B2. Although the claims at issue are not identical, they are not patentably distinct from each other for the following reasons:
Pending Claim
Patented Claim
Explanation
1. A method of operation of an autonomous vehicle in an environment, comprising:
1. A method of operation of an autonomous vehicle in an environment, comprising:
The limitations are the same.
determining a set of inputs using a sensor suite of the autonomous vehicle, the set of inputs comprising an environmental agent instance identifier and a state history associated with the environmental agent instance identifier;
determining a set of inputs using a sensor suite of the autonomous vehicle, the set of inputs comprising an environmental agent instance identifier and a state history associated with the environmental agent instance identifier;
The limitations are the same.
based on the set of inputs, determining a set of environmental policies for the environmental agent instance identifier;
based on the set of inputs, determining a set of multiple environmental policies for the environmental agent instance identifier;
The patented limitation is slightly narrower, since it further specifies that the set contains multiple elements.
for each environmental policy of the set:
for each environmental policy of the set of multiple environmental policies:
The patented limitation is slightly narrower.
determining a historical score by comparing a state history of the environmental agent to a reference trajectory associated with the environmental policy; and
determining a historical score by comparing the state history associated with the environmental agent instance identifier to a reference trajectory associated with the environmental policy; and
The patented limitation is slightly narrower.
determining a feasibility score by a forward simulation of the environmental policy; and
determining a feasibility score by a forward simulation of the environmental policy, wherein the forward simulation of each environmental policy comprises a closed-loop simulation for a deterministic controller associated with the environmental policy, wherein the feasibility score is determined based on a time-derivative of an accumulation of lateral error between the reference trajectory and the forward simulation; and aggregating the historical score and the feasibility score for each environmental policy of the set of multiple environmental policies into a respective aggregates core, wherein producing the respective aggregate score comprises multiplying the respective historical score and the respective feasibility score;
The patented limitation is significantly narrower, but nonetheless, still contains all the limitations of the pending claim.
determining an ego policy by evaluating a set of ego policies for the autonomous vehicle relative to the set of environmental policies, based on the feasibility scores and the historical scores; and
determining an ego policy by evaluating a set of ego policies for the autonomous vehicle relative to the set of multiple environmental policies, based on the feasibility scores and the historical scores, wherein the evaluation of the set of ego policies relative to the set of multiple environmental policies is weighted based on the aggregate score of each environmental policy of the set of multiple environmental policies; and
The patented limitation is significantly narrower, but nonetheless, still contains all the limitations of the pending claim.
operating the autonomous vehicle based on the ego policy.
controlling driving of the autonomous vehicle based on the ego policy.
The patented limitation is narrower, since “controlling driving” is a type of “operating”.
Because all of the limitations (or narrowed versions thereof) of the pending claim appear in the patented claim, the pending claim is accordingly rejected under the doctrine of non-statutory double patenting.
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 1 is rejected under 35 U.S.C. 102(a)(1) as being anticipated by Olson et al. (US 20180268281 A1), hereinafter referred to as Olson.
Regarding claim 1, Olson discloses A method of operation (See at least Fig. 3 in Olson: Olson discloses that a flowchart of an embodiment of the MPDM apparatus [See at least Olson, 0082]) of an autonomous vehicle in an environment (Olson discloses that the controlled object may be a vehicle, a robot, or any other autonomous object that is configured to move through an environment [See at least Olson, 0028]), comprising:
determining a set of inputs (See at least Fig. 3 in Olson: Olson discloses that at step 304, control receives state data for each of the monitored objects 208, 212 [See at least Olson, 0082]) using a sensor suite of the autonomous vehicle (Olson discloses that the state data is obtained by the perception module 112 [See at least Olson, 0082]), the set of inputs comprising an environmental agent instance identifier and a state history associated with the environmental agent instance identifier (See at least Fig. 3 in Olson: Olson discloses that at step 304, control receives state data for each of the monitored objects 208, 212 [See at least Olson, 0082]. It will therefore be appreciated that each of the monitored objects is identified and that at least one state, which may be regarded as a state history, is gathered for each of them);
based on the set of inputs, determining a set of environmental policies for the environmental agent instance identifier (See at least Fig. 3 in Olson: Olson discloses that control chooses a policy to evaluate 300 from all of the potential policies 136 [See at least Olson, 0082]. Olson further discloses that seed states for each of the monitored objects 208, 212 are generated at 308 using the seed state generator 116 [See at least Olson, 0082]. Olson further discloses that simulator 120 then simulates using the chosen policy and the seed states at 312 [See at least Olson, 0082]. Olson further discloses that the cost function is calculated as a combination of blame for disturbing objects in the environment as well as progress towards the target 216 [See at least Olson, 0082]. Olson further discloses that control determines whether each policy 136 has been simulated 336 [See at least Olson, 0084]. Olson further discloses that, if not, control returns to the beginning to select a different policy at 200 [See at least Olson, 0084]. It will be appreciated that, since each of a plurality of ego vehicle policies is simulated, and the objects’ responses to each of those policies are also simulated, then each response of an object may be regarded as an environmental policy of an environmental agent and there are multiple responses for each object);
for each environmental policy of the set (See at least Fig. 3 in Olson: Olson discloses that control determines whether each policy 136 has been simulated 336 [See at least Olson, 0084]. Olson further discloses that, if not, control returns to the beginning to select a different policy at 200 [See at least Olson, 0084]. It will be appreciated that, since each of a plurality of ego vehicle policies is simulated, and the objects’ responses to each of those policies are also simulated, then each response of an object may be regarded as an environmental policy of an environmental agent):
determining a historical score by comparing a state history of the environmental agent to a reference trajectory associated with the environmental policy (Olson teaches that the probabilistic estimate P(x.sub.0) is based on past observations of the pedestrians' positions [See at least Olson, 0052]. Olson further teaches that several methods can be used for P(x.sub.0) based on past trajectories of agents [See at least Olson, 0052]. Since this probably is therefore derived from observed states and previous trajectories, it may be regarded as a historical score); and
determining a feasibility score by a forward simulation of the environmental policy (Olson discloses that the forward simulation can be conceptualized as a deep network that outputs a trajectory cost C(X(x.sub.0)) based on the input initial configuration [See at least Olson, 0067]); and
determining an ego policy (See at least Fig. 3 in Olson: Olson discloses that the policy with the best score is selected at 344 [See at least Olson, 0085]) by evaluating a set of ego policies for the autonomous vehicle relative to the set of environmental policies (See at least Fig. 3 in Olson: Olson teaches that once control determines that each policy has been simulated at 336, then scores are determined for each policy at 340 [See at least Olson, 0085]. Olson further teaches that the policy with the best score is selected at 344 [See at least Olson, 0085]. Olson further teaches that the best score can be described as the score indicating the fewest number of the most benign high-cost events [See at least Olson, 0085]), based on the feasibility scores and the historical scores (See at least Fig. 3 in Olson: Olson teaches that step 320 controls the number of times the seed states are perturbed and simulated to determine which policy results in the most benign high-cost events [See at least Olson, 0083]. Olson further teaches that the outcome quantifier 128 then quantifies a perturbed outcome as the product of the perturbed cost and the perturbed probability at 332 [See at least Olson, 0084]. It will therefore be appreciated that the number of benign high-cost events, which is the “evaluation” is based on the product of the (historical) probability and the (feasibility) cost calculated in each iteration of the state model); and
operating the autonomous vehicle based on the ego policy (See at least Fig. 3 in Olson: Olson discloses that once the policy is selected, control issues a command associated with the policy to the controlled object 100 at 348 [See at least Olson, 0085]. Olson further discloses that the commands may be a command to accelerate, decelerate, etc. [See at least Olson, 0085]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NAEEM T ALAM whose telephone number is (571)272-5901. The examiner can normally be reached M-F, 9am-5pm.
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/NAEEM TASLIM ALAM/Examiner, Art Unit 3668
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