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 .
This application has been examined. Claims 1-20 are pending.
The prior art submitted on 12/17/24 has been considered.
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.
Claims 1-20, are rejected under 35 U.S.C. 103 as being unpatentable over Yoon et al. (US 2017/0096167 A1) in view of Moosaei et al. (US 2018/0164830 A1).
As per claims 1, and 10, Yoon et al. disclose an operating method of an electronic device, the operating method comprising: identifying a parking spot to park a moving object (see at least [0047] disclose the controller 170 recognizes a parking-available parking slot); inputting the parking spot and odometry information representing a position of the moving object relative to the parking spot to a first controller, the first controller inferring a first output from the parking spot and the odometry information (see at least [0051-0053] disclose when the target parking slot is determined, the controller 170 sets a parking start position; and para. [0067-0068] disclose the minimum turning radius, and movement distance of vehicle, this represent vehicle odometry information, and the controller 170 implies first AI model); controlling driving of the moving object based on the first output obtained by the first controller (see at least [0051-0056] disclose the controller 170 control a steering device, a braking device, and a driving device according to parking guidance to perform autonomous parking);
inputting an image obtained by a camera of the moving object to a second controller, the second controller inferring a second output from the image; and controlling the driving of the moving object to drive to the parking spot based on the second output obtained by the second controller (see at least [0036-0040] disclose image processor 120 generates a top view image using images captured through the image obtainer 110 and controlling the driving of the moving object to the parking spot, here the image processor 120 implied the second AI model). Yoon et al. do not explicitly said first and second AI model. However, as cited as above, the controller 170 implies first AI model because the controller 170 inferring a first output from the parking spot and the odometry information; and the image processor 120 implies the second AI model because the image processor 120 inferring a second output from the image). Furthermore, the computer system uses at least one of machine learning, AI model for assisted or automatic parking of vehicle is well known in the art. The second reference to Moosaei et al. disclose the computer system to recognize parking spot, vehicle location and/or orientation and image of the moving object using at least one AI model for assisted or automatic parking of vehicle (see at least para. [0032-0037], [0043-0051], and [0055-0059]). It 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 to modify the teach of Yoon et al. by combining the AI model for determining whether a condition precedent for entering the parking lot for assisted or autonomous parking of a vehicle.
As per claim 2, Yoon et al. disclose the first output is determined based on the parking spot and the odometry information, and wherein the first output comprises: an indication of whether the moving object reached a spot from which the moving object is able to be parked into the parking spot by a predetermined number of forward maneuvers and/or backward maneuvers, and steering and speed settings by which to control the moving object to find and drive to the spot (see at least [0051-0060] disclose when the vehicle moves to the position at which the vehicle is able to enter the target parking slot, the controller 170 guides the driver to turn the steering wheel full turn in the opposite direction to park the vehicle in the target parking slot with a predetermined number of forward and/or backward maneuvers).
As per claim 3, Yoon et al. disclose wherein the predetermined number is one (see at least [0059]).
As per claim 4, Yoon et al. disclose the controlling of the driving of the moving object and the inputting of the image by the camera to the second controller comprises: when it is determined that the moving object reaches the spot, inputting the image to the second controller (see at least [0047] disclose when the parking guidance mode is entered, the controller 170 obtains an AVM image around the vehicle through the image obtainer 110 and the image processor 120).
As per claim 5, Yoon et al. disclose based on the first output, determining that the moving object has reached the spot, controlling the driving of the moving object based on the steering and the speed, updating the odometry information of the moving object driven after the moving object has driven based on the steering and the speed, and inputting the updated odometry information and the parking spot to the first controller (see at least [0051-0060] disclose when the vehicle moves to the position at which the vehicle is able to enter the target parking slot, the controller 170 guides the driver to turn the steering wheel full turn in the opposite direction to park the vehicle in the target parking slot; and para. [0067-0072] disclose the vehicle turning radius and movement distance).
As per claim 6, Yoon et al. disclose the second output comprises steering and speed to control the moving object to drive to the parking spot determined based on the image obtained by the camera (see at least [0036-0040] disclose the second output of image processor 120 comprises vehicle velocity, a heading angle, a gear stage, a steering angle to control the moving vehicle to drive to the parking spot determined based on the image obtained by the camera).
As per claim 7, Yoon et al. disclose the parking spot is determined based on odometry information of the moving object updated according to the driving of the moving object after the parking spot is initially identified to park the moving object (see at least [0067-0072] disclose vehicle turning radius and movement distance positions).
As per claim 8, Yoon et al. disclose the first controller is trained to output information about whether the moving object reaches a reference target spot in which the moving object is able to be parked in a reference parking spot by a predetermined number of forward maneuvers and/or backward maneuvers, and reference steering and reference speed to cause the moving object to find and drive to the reference target spot by receiving the reference parking spot and reference odometry information in a first training data set (see at least [0054-0064], and [0067-0072], all para. disclose a relationship between a parking slot entry of a vehicle and a central trace of a rear axle in parking a vehicle).
As per claim 9, Yoon et al. disclose the second controller is trained to output reference steering and reference speed to cause the moving object to drive to a reference parking spot from a reference target spot from which the moving object is able to be parked into the reference parking spot by a predetermined number of forward maneuvers and/or backward maneuvers by receiving a reference image in a second training data set (see at least [0051-0060] disclose when the vehicle moves to the position at which the vehicle is able to enter the target parking slot, the controller 170 guides the driver to turn the steering wheel full turn in the opposite direction to park the vehicle in the target parking slot with a predetermined number of forward and/or backward maneuvers).
As per claim 11, Yoon et al. disclose a non-transitory computer-readable storage medium storing one or more instructions that, when executed by a processor, cause the processor to perform the method of claim 1 (see at least [0036-0040]).
As per claim 12, Yoon et al. disclose an electronic device comprising: at least one memory comprising instructions; and one or more processors configured to execute the instructions, wherein the instructions are configured to, when executed by the one or more processors, cause the one or more processors to: determine a parking spot (see at least [0047] disclose the controller 170 recognizes a parking-available parking slot); (see at least [0047] disclose the controller 170 recognizes a parking-available parking slot); perform a first parking maneuver in a first direction by repeatedly: having a first controller model infer from the parking spot a first output comprising at least a speed and a direction, driving the moving object according to the speed and direction, obtaining odometry of the moving object, and determining from the first output if a first condition is satisfied (see at least [0051-0053] disclose when the target parking slot is determined, the controller 170 sets a parking start position; and para. [0067-0068] disclose the minimum turning radius, and movement distance of vehicle, this represent vehicle odometry information, and the controller 170 implies first AI model); and in response to determining that the first condition is satisfied, performing a second parking maneuver in a second direction opposite to the first direction by repeatedly: obtaining an image, having a second controller model infer from the image a second output comprising a speed and direction, driving the moving object according to the speed and direction, and determining if the moving object has reached the parking spot (see at least [0036-0040] disclose image processor 120 generates a top view image using images captured through the image obtainer 110 and controlling the driving of the moving object to the parking spot, here the image processor 120 implied the second AI model). Yoon et al. do not explicitly said first and second AI model. However, as cited as above, the controller 170 implies first AI model because the controller 170 inferring a first output from the parking spot and the odometry information; and the image processor 120 implies the second AI model because the image processor 120 inferring a second output from the image). Furthermore, the computer system uses at least one of machine learning, AI model for assisted or automatic parking of vehicle is well known in the art. The second reference to Moosaei et al. disclose the computer system to recognize parking spot, vehicle location and/or orientation and image of the moving object using at least one AI model for assisted or automatic parking of vehicle (see at least para. [0032-0037], [0043-0051], and [0055-0059]). It 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 to modify the teach of Yoon et al. by combining the AI model for determining whether a condition precedent for entering the parking lot for assisted or autonomous parking of a vehicle.
As per claim 13, Yoon et al. disclose determining from the first output if a first condition is satisfied comprises determining if the moving object can reach the parking spot from a current position of the moving object (see at least [0097-0104] disclose determine whether the vehicle has reached the parking spot from a current position).
As per claim 14, Yoon et al. disclose the second controller network does not use the determined parking spot to infer the second outputs (see at least [0037-0039] disclose the image processor 120 generates a top view image using images captured through the image obtainer 110).
As per claim 15, Yoon et al. disclose the odometry information of the moving object is determined based on sensors of the moving object (see at least [0040] disclose the sensors 130 sense vehicle data includes a vehicle velocity, a heading angle, a gear stage, a steering angle, and the like; and para. [0067-0072] disclose vehicle turning radius, and movement distance).
As per claim 16, Yoon et al. disclose the first parking maneuver is performed without using the second controller network, and the second parking maneuver is performed without using the first controller network (see at least [0051-0063] disclose steering guidance to perform vehicle maneuver to the parking spot).
As per claim 17, Yoon et al. disclose the second outputs each comprise steering and speed to control the moving object to drive toward the parking spot based on the image obtained by the camera (see at least [0036-0040] disclose image processor 120 generates a top view image using images captured through the image obtainer 110 and controlling the driving of the moving object to the parking spot).
As per claim 18, Yoon et al. disclose the parking spot is determined based on odometry information updated according to the driving of the moving object after the parking spot is initially identified to park the moving object (see at least [0067-0072] disclose the parking spot is determined based on vehicle turning radius and movement distance; and para. [0083-0089]).
As per claim 19, Yoon et al. disclose the first controller network model is trained to output information indicating whether the moving object has reached a reference target spot from which the moving object is able to be parked into a reference parking spot by a predetermined number of forward maneuvers and/or backward maneuvers, and reference steering and reference speed to cause the moving object to find and drive to the reference target spot by receiving the reference parking spot and reference odometry information in a first training data set (see at least [0097-0108] disclose determine whether the vehicle has reached a target position).
As per claim 20, Yoon et al. disclose the second controller network model is trained to output reference steering and reference speed to cause the moving object to drive to a reference parking spot from a reference target spot from which the moving object is able to be parked into the reference parking spot by one forward maneuver or one backward maneuver (see at least [0051-0064] disclose steering guidance to control vehicle enter to parking spot).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure:
. Schneider et al. (US 2012/0197492 A1)
. Solar (US 2021/0370915 A1)
. Vassilovski et al. (US 2020/0342760 A1)
Kentley-Klay (10384718)
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DALENA TRAN whose telephone number is (571)272-6968. The examiner can normally be reached M-F 7AM-5PM.
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/DALENA TRAN/Primary Examiner, Art Unit 3657
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