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 .
Response to Arguments
Applicant’s arguments, see Pages 5-7, filed September 1, 2026, with respect to double patenting rejections have been fully considered and are persuasive. The double patenting rejections been withdrawn.
Applicant’s arguments, see Pages 7-9, filed September 1, 2026, with respect to 101 rejections have been fully considered and are persuasive. The 101 rejections have been withdrawn.
Applicant’s arguments, see Pages 9-12, filed September 1, 2026, with respect to the rejection(s) of claim(s) 1 under 35 U.S>C. 102 and/or 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Yamanouchi et al. (US 20250091623; hereinafter Yamanouchi).
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 (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 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.
The factual inquiries 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.
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(s) 1 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ponomarev et al. (US 20250026370; hereinafter Ponomarev; already of record) in view of Yamanouchi et al. (US 20250091623; hereinafter Yamanouchi).
In regards to claim 1, Ponomarev discloses of an apparatus (“A method and a system for planning motion of a Self-Driving Car (SDC) are provided. The method comprises: receiving sensed data representative of the surroundings of the SDC; feeding the sensed data to a plurality of machine-learning (ML) models, the feeding comprising: feeding the sensed data to a first ML model to generate a first prediction for a given object in the surroundings of the SDC; in response to a time for generating the first prediction being higher than a predetermined threshold: planning the motion of the SDC based on the first prediction; and in response to the time for generating the first prediction being lower than the first predetermined time period threshold: feeding the first prediction along with the sensed data to a second ML model to generate a second prediction for the given object; and planning the motion of the SDC based on the second prediction.” (Abstract)) comprising:
a processor (“With reference to FIG. 1, there is depicted a schematic diagram of a computer system 100 suitable for use with some implementations of the present technology. The computer system 100 includes various hardware components including one or more single or multi-core processors collectively represented by a processor 110, a solid-state drive 120, and a memory 130, which may be a random-access memory or any other type of memory.” (Para 0071)), wherein
the processor is configured to:
using a sensor, environmental information regarding at least one of environment around a current location of a moving object, and environment ahead of the moving object in a travel direction, the moving object being capable of moving by unmanned driving (“It should be noted that a variety of sensors and systems may be used by the electronic device 210 for gathering information about surroundings 250 of the vehicle 220. As seen in FIG. 2, the vehicle 220 may be equipped with a plurality of sensor systems 280. It should be noted that different sensor systems from the plurality of sensor systems 280 may be used for gathering different types of data regarding the surroundings 250 of the vehicle 220.” (Para 0084), “In other non-limiting embodiments of the present technology, the camera sensor 290 is configured to capture an image (or a series of images) that represent approximately 180 degrees of the surroundings 250 around the vehicle 220 that are along a movement path of the vehicle 220. In yet other non-limiting embodiments of the present technology, the camera sensor 290 is configured to capture the image data that represent approximately 360 degrees of the surroundings 250 around the vehicle 220 that are along a movement path of the vehicle 220 (in other words, the entirety of the surrounding area around the vehicle 220).” (Para 0088), “One of the technical challenges associated with the SDC's is their ability to predict, or otherwise determine trajectories of other road users (other vehicles, for example) travelling in the surrounding area of the SDC, for example, in neighbouring lanes. When a given vehicle, travelling, for example, ahead of the SDC in a neighbouring lane, is about to perform a maneuver (such as turning left or right), its trajectory may overlap and/or intersect (at least partially) with the trajectory of the SDC, which may cause high risk of collision between the SDC and one of the other vehicles (including the given one) in the surrounding area. Consequently, this may require the SDC to take corrective measures, be it braking or otherwise active accelerating resulting in building the SDC trajectory ensuring minimal risk of an accident.” (Para 0005)); and
generate value data using the acquired environmental information, the value data including at least one of a braking-related value and a work- related value (“One of the technical challenges associated with the SDC's is their ability to predict, or otherwise determine trajectories of other road users (other vehicles, for example) travelling in the surrounding area of the SDC, for example, in neighbouring lanes. When a given vehicle, travelling, for example, ahead of the SDC in a neighbouring lane, is about to perform a maneuver (such as turning left or right), its trajectory may overlap and/or intersect (at least partially) with the trajectory of the SDC, which may cause high risk of collision between the SDC and one of the other vehicles (including the given one) in the surrounding area. Consequently, this may require the SDC to take corrective measures, be it braking or otherwise active accelerating resulting in building the SDC trajectory ensuring minimal risk of an accident.” (Para 0005), “In at least some non-limiting embodiments of the present technology, the electronic device 210 is communicatively coupled to control systems of the vehicle 220. The electronic device 210 could be arranged and configured to control different operations systems of the vehicle 220, including but not limited to: an ECU (engine control unit), steering systems, braking systems, and signaling and illumination systems (i.e. headlights, brake lights, and/or turn signals). In such an embodiment, the vehicle 220 could be a self-driving vehicle.” (Para 0074), “As it can be appreciated from FIG. 4, as the vehicle 220 approaches an intersection in the given road section 402, it may be configured, according to a predetermined (prior) movement trajectory thereof, to make a right maneuver 404 to an intersecting road. However, to avoid collision with an upcoming vehicle 420 driving down the intersecting road in a straight direction 406, the vehicle 220 must be capable of (i) detecting the upcoming vehicle 420; and (ii) taking certain corrective measures with respect to the prior predetermined movement trajectory, such as one of slowing down, accelerating, or breaking, as an example, thereby re-determining the movement trajectory for the vehicle 220.” (Para 0112)),
the braking-related value including at least one of a braking control value, and a braking correction value (“One of the technical challenges associated with the SDC's is their ability to predict, or otherwise determine trajectories of other road users (other vehicles, for example) travelling in the surrounding area of the SDC, for example, in neighbouring lanes. When a given vehicle, travelling, for example, ahead of the SDC in a neighbouring lane, is about to perform a maneuver (such as turning left or right), its trajectory may overlap and/or intersect (at least partially) with the trajectory of the SDC, which may cause high risk of collision between the SDC and one of the other vehicles (including the given one) in the surrounding area. Consequently, this may require the SDC to take corrective measures, be it braking or otherwise active accelerating resulting in building the SDC trajectory ensuring minimal risk of an accident.” (Para 0005), “In at least some non-limiting embodiments of the present technology, the electronic device 210 is communicatively coupled to control systems of the vehicle 220. The electronic device 210 could be arranged and configured to control different operations systems of the vehicle 220, including but not limited to: an ECU (engine control unit), steering systems, braking systems, and signaling and illumination systems (i.e. headlights, brake lights, and/or turn signals). In such an embodiment, the vehicle 220 could be a self-driving vehicle.” (Para 0074), “As it can be appreciated from FIG. 4, as the vehicle 220 approaches an intersection in the given road section 402, it may be configured, according to a predetermined (prior) movement trajectory thereof, to make a right maneuver 404 to an intersecting road. However, to avoid collision with an upcoming vehicle 420 driving down the intersecting road in a straight direction 406, the vehicle 220 must be capable of (i) detecting the upcoming vehicle 420; and (ii) taking certain corrective measures with respect to the prior predetermined movement trajectory, such as one of slowing down, accelerating, or breaking, as an example, thereby re-determining the movement trajectory for the vehicle 220.” (Para 0112)), and
the work-related value including at least one of a work control value, a work setting value, and a work correction value, wherein
(i) the braking control value is a control value regarding braking of the moving object and is an indication value to specify a negative acceleration in a travelling control signal for causing the moving object to move by the unmanned driving, (ii) the braking correction value being is a correction value to correct the braking control value (“One of the technical challenges associated with the SDC's is their ability to predict, or otherwise determine trajectories of other road users (other vehicles, for example) travelling in the surrounding area of the SDC, for example, in neighbouring lanes. When a given vehicle, travelling, for example, ahead of the SDC in a neighbouring lane, is about to perform a maneuver (such as turning left or right), its trajectory may overlap and/or intersect (at least partially) with the trajectory of the SDC, which may cause high risk of collision between the SDC and one of the other vehicles (including the given one) in the surrounding area. Consequently, this may require the SDC to take corrective measures, be it braking or otherwise active accelerating resulting in building the SDC trajectory ensuring minimal risk of an accident.” (Para 0005), “In at least some non-limiting embodiments of the present technology, the electronic device 210 is communicatively coupled to control systems of the vehicle 220. The electronic device 210 could be arranged and configured to control different operations systems of the vehicle 220, including but not limited to: an ECU (engine control unit), steering systems, braking systems, and signaling and illumination systems (i.e. headlights, brake lights, and/or turn signals). In such an embodiment, the vehicle 220 could be a self-driving vehicle.” (Para 0074), “As it can be appreciated from FIG. 4, as the vehicle 220 approaches an intersection in the given road section 402, it may be configured, according to a predetermined (prior) movement trajectory thereof, to make a right maneuver 404 to an intersecting road. However, to avoid collision with an upcoming vehicle 420 driving down the intersecting road in a straight direction 406, the vehicle 220 must be capable of (i) detecting the upcoming vehicle 420; and (ii) taking certain corrective measures with respect to the prior predetermined movement trajectory, such as one of slowing down, accelerating, or breaking, as an example, thereby re-determining the movement trajectory for the vehicle 220.” (Para 0112); wherein it is noted that the work-related values are optional due to the “at least one of” language), (iii) the work control value is a control value for controlling a work device performing an operation on the moving object and is a parameter of at least one of a position of an arm provided in the work device and a movement of the arm, (iv) the work setting value is a setting value of at least one of the position of the arm and the movement of the arm of the work device, and (v) the work correction value is a correction value to correct the work control value
the environmental information includes three-dimensional point cloud information of the environment ahead of the moving object (“More specifically, for determining the object class of the given surrounding object, the MLA 260 can be configured to determine a plurality of object features describing the given surrounding object. Merely as an example, and in no way as a limitation, in case where the given surrounding object is the upcoming vehicle 420, the object features can include, without limitation: (i) a type of the given surrounding object, such as a movable object; (ii) a type of the movable object, such as an inanimate object; (iii) a type of the movable inanimate object, such as a vehicle; (iv) a brand and a model of the upcoming vehicle 420; (v) an issue year of the upcoming vehicle 420; (vi) a body type of the upcoming vehicle 420, such as a sedan, a hatchback, a wagon vehicle, a minivan and others; (vii) a control type of the upcoming vehicle 420, such as traditional (operated by a driver) or driverless (that is, an other SDC); (viii) a current speed of the upcoming vehicle 420 in the straight direction 406; (ix) a distance 408 from the vehicle 220 to the upcoming vehicle 420; and others.” (Para 0115), “With reference to FIG. 3, there is depicted a schematic diagram of a LiDAR data acquisition procedure 302, executed by the processor 110 of the electronic device 210, for generating a 3D point cloud data 310 representative of surrounding object present in the surroundings 250 of the vehicle 220, in accordance with certain non-limiting embodiments of the present technology.” (Para 0105), “According to certain non-limiting embodiments of the present technology, to detect the surrounding objects of the vehicle 220, such as those in the given road section 402 depicted in FIG. 4, using the MLA 260 as described above, the processor 110 can be configured to: (i) receive, from the plurality of sensor systems 280 of the vehicle 220, the sensed data representative of the given road section 402, such as at least one of a respective image (not separately labelled) from the camera sensor 290 and the 3D point cloud 312 from the LiDAR sensor 300; (ii) generate, based on the sensed data of the given road section 402, a respective in-use feature vector; and (iii) feed the respective in-use feature vector to each one of the plurality of ML models.” (Para 0176), see also Figs 3-4 and 7), and
the processor is further configured to:
…
brake the moving object for the operation on the moving object by controlling an actuator provided in the moving object using the generated value data (“One of the technical challenges associated with the SDC's is their ability to predict, or otherwise determine trajectories of other road users (other vehicles, for example) travelling in the surrounding area of the SDC, for example, in neighbouring lanes. When a given vehicle, travelling, for example, ahead of the SDC in a neighbouring lane, is about to perform a maneuver (such as turning left or right), its trajectory may overlap and/or intersect (at least partially) with the trajectory of the SDC, which may cause high risk of collision between the SDC and one of the other vehicles (including the given one) in the surrounding area. Consequently, this may require the SDC to take corrective measures, be it braking or otherwise active accelerating resulting in building the SDC trajectory ensuring minimal risk of an accident.” (Para 0005), “In at least some non-limiting embodiments of the present technology, the electronic device 210 is communicatively coupled to control systems of the vehicle 220. The electronic device 210 could be arranged and configured to control different operations systems of the vehicle 220, including but not limited to: an ECU (engine control unit), steering systems, braking systems, and signaling and illumination systems (i.e. headlights, brake lights, and/or turn signals). In such an embodiment, the vehicle 220 could be a self-driving vehicle.” (Para 0074), “As it can be appreciated from FIG. 4, as the vehicle 220 approaches an intersection in the given road section 402, it may be configured, according to a predetermined (prior) movement trajectory thereof, to make a right maneuver 404 to an intersecting road. However, to avoid collision with an upcoming vehicle 420 driving down the intersecting road in a straight direction 406, the vehicle 220 must be capable of (i) detecting the upcoming vehicle 420; and (ii) taking certain corrective measures with respect to the prior predetermined movement trajectory, such as one of slowing down, accelerating, or breaking, as an example, thereby re-determining the movement trajectory for the vehicle 220.” (Para 0112)).
However, Ponomarev does not specifically disclose of when a number of points in the three-dimensional point cloud information is a first point cloud number, generate the value data including the braking-related value such that a braking force per unit time of the moving object becomes larger compared to when the number of points is a second point cloud number, the second point cloud number being larger than the first point cloud number.
Yamanouchi, in the same field of endeavor, teaches of when a number of points in the three-dimensional point cloud information is a first point cloud number, generate the value data including the braking-related value such that a braking force per unit time of the moving object becomes larger compared to when the number of points is a second point cloud number, the second point cloud number being larger than the first point cloud number (“As described above, the score threshold value in the case of a bad weather is set to be lower than the score threshold value in the case of a good weather. In the example of FIG. 4, the score threshold value in the case of a bad weather is set to be 0.2 points lower than the score threshold value in the case of a good weather. That is, there is a problem that the number of points in the three-dimensional point cloud that can be generated by the LiDAR apparatus 3 per unit time decreases in the case of a bad weather. In other words, the reliability of the sensing by the LiDAR apparatus 3 decreases in the case of a bad weather. Therefore, since it is considered that the reliability of the detection score output from the second obstacle detection unit 7 is decreased in the case of a bad weather, prevention of collision between the train 1 and the obstacle is prioritized, that is, it is easier to decelerate or stop the train 1, as compared with the case of a good weather.” (Para 0056)).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the braking related value, as taught by Ponomarev, to include adjusting the braking force to be larger if a number of points in a three point cloud is lower, as taught by Yamanouchi, with a reasonable expectation of success in order to avoid a collision with an obstacle due to poor sensor reliability (Yamanouchi Para 0056).
Allowable Subject Matter
Claim 6 allowed.
The following is an examiner’s statement of reasons for allowance:
In regards to claim 6, the closest prior art of record is Ponomarev et al. (US 20250026370; hereinafter Ponomarev; already of record) in view of Zha et al. (US 20250050893) in view of Yamanouchi et al. (US 20250091623; hereinafter Yamanouchi). Ponomarev in view of Zha further in view of Yamanouchi teaches of an apparatus comprising:
a processor, wherein
the processor is configured to:
acquire, using a sensor, environmental information regarding at least one of environment around a current location of a moving object, and environment ahead of the moving object in a travel direction, the moving object being capable of moving by unmanned driving; and
generate value data using the acquired environmental information, the value data including at least one of a braking-related value and a work-related value,
the braking-related value including at least one of a braking control value and a braking correction value, and
the work-related value including at least one of a work control value, a work setting value, and a work correction value, wherein
(i) the braking control value is a control value regarding braking of the moving object and is an indication value to specify a negative acceleration in a travelling control signal for causing the moving object to move by the unmanned driving, (ii) the braking correction value is a correction value to correct the braking control value, (iii) the work control value is a control value for controlling a work device performing an operation on the moving object and is a parameter of at least one of a position of an arm provided in the work device and a movement of the arm, (iv) the work setting value is a setting value of at least one of the position of the arm and the movement of the arm of the work device, and (v) the work correction value is a correction value to correct the work control value,
the environmental information includes three-dimensional point cloud information of the environment ahead of the moving object.
However, the prior art does not fully teach of the processor is further configured to:
when a number of points in the three-dimensional point cloud information is a first point cloud number, generate the value data including the work-related value such that the operation is performed by the work device at a position further forward in the travel direction of the moving object compared to when the number of points is a second point cloud number, the second point cloud number being larger than the first point cloud number, and
cause the work device to perform the operation on the moving object by controlling at least one of the position of the arm and the movement of the arm using the generated value data. It is noted that the prior art teaches of a work device to perform an operation on a moving vehicle, where the movement of the moving vehicle is adjusted based on the number of points from a three-dimensional point cloud. However, the prior art does not specifically teach of having the work device have a position further forward when the number of points in the three-dimensional point cloud is a first point cloud number, as compared to the movement of the work device when there is a second point cloud number that is larger than the first point cloud number, in combination with the remaining claim limitations. Therefore the claim is allowable.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Gupta et al. (US 11594017) discloses of determining if there is a weather event based on the number of points in a point cloud of a lidar sensor.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Kyle J Kingsland whose telephone number is (571)272-3268. The examiner can normally be reached Monday-Friday from 8:00-4:30.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Abby Flynn can be reached at (571) 272-9855. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/KYLE J KINGSLAND/Primary Examiner, Art Unit 3663
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