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 . Claims 1-2, 4-5, 7-8, 10, 11-12, 14-15, 17-20, and 22 are pending and examined below. This action is in response to the claims filed 12/9/25.
Continued Examination Under 37 CFR 1.114
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/9/25 has been entered.
Response to Amendment
Applicant’s arguments, see Applicant Remarks 35 U.S.C. § 103 filed on 12/9/25, regarding 35 U.S.C. § 103 rejections have been found persuasive.
Upon further search considerations, new grounds of rejection are made in view of Beer et al. (US 2019/0250641) below.
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 1-2, 7-8, 10, 12, and 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Liu et al. (US 2019/0265734) in view of Moore et al. (US 2019/0094866) and Beer et al. (US 2019/0250641).
Regarding claims 1, 10, and 19, Liu discloses a system and method for object detection and movement adjustment maneuvers including a method/mobile device, comprising: a processor; and a memory storing computer instructions for causing the processor to perform acts comprising (¶138):
obtaining a cost map of a moving area and a target path of the mobile device moving in the moving area (¶72-75, ¶97-98 and Fig. 12 – coordinate system corresponding to the recited cost map of the moving area and initial trajectory corresponding to the recited target path of the mobile device moving in the area);
based on the cost map, determining a current target distance between the mobile device and an obstacle, and a current turning curvature of the mobile device in response to determining that the mobile device moving along the target path (¶118 - z-distance between the obstacle and the moveable object corresponding to the recited current target distance between the mobile object and an obstacle and sideways maneuvers corresponding to the recited current turning curvature of the mobile device based on the coordinate system identified objects and positioning of the moveable object);
determining a target speed of the mobile device based on the current target distance, the current turning curvature, and a maximum limiting speed of the mobile device (¶122-123 and ¶144 – movement speed is determined based on distance to the object corresponding to the recited current target distance, clearance distance corresponding to the recited turning curvature, and implicit capabilities of the moveable object corresponding to the recited maximum limiting speed of the mobile device); and
controlling the mobile device to move at the target speed (¶122-123 and ¶144 – moveable device is controlled based on the adjusted movement plan);
wherein, based on the cost map, determining the current target distance between the mobile device and the obstacle comprises (¶118 - z-distance between the obstacle and the moveable object corresponding to the recited current target distance between the mobile object and an obstacle):
based on the cost map, determining obstacle data within a preset range in front of the mobile device (¶115-118 - predetermined distance threshold for emergency obstacle avoidance maneuvers corresponding to the recited obstacle data within a preset range in front of the mobile device based on the coordinate system):
obtaining the current target distance based on the first distance and the second distance (¶115-118 and ¶163-167 – a first component that is parallel to the original movement path and a second component that is perpendicular to the original movement path are utilized to determine the long range obstacle avoidance maneuver including the current target distance).
Liu does not explicitly disclose utilizing parameter correlations or weighted values for adjusting speed components however Moore discloses a dynamic window approach using cost critic collision avoidance functions including wherein determining a straight-line travelling speed component of the mobile device based on the current target distance and the maximum limiting speed, wherein the straight-line travelling speed component is positively correlated with the current target distance (¶89 and ¶99-105 – v is the forward or linear motion of the robot corresponding to the recited straight line traveling speed component is calculated based on maximum safe speed corresponding to the recited maximum limiting speed and a path cost critic weighting the distance of the robot from the goal path as well as inflated obstacles in the path where cost to avoid close proximity to obstacles discloses the positive correlation between speed and current target distance);
determining a turning speed component of the mobile device based on the current turning curvature and the maximum limiting speed, wherein the turning speed component is negatively correlated with the current turning curvature (¶99-105 – ω is the rotational velocity of the robot corresponding to the recited turning speed component of the mobile device is calculated based on maximum safe speed corresponding to the recited maximum limiting speed and higher costs to changes in the magnitude or direction of rotation corresponding to the recited negative correlation between speed and current turning curvature); and
based on a preset straight-line travelling speed weight and a preset turning speed weight, performing a weighted fusion processing on the straight-line travelling speed component and the turning speed component to obtain the target speed of the mobile device (¶99-105 – objective function includes heading, distance, and velocity components all with different dynamic weightings based on preset critic weightings corresponding to the recited weighted fusion of the components).
The combination of the system and method for object detection and movement adjustment maneuvers utilizing a coordinate system of Liu with the weighted velocity correlations and calculations of Moore in order to provide a computationally efficient method for robot navigation considering both moving and fixed obstacles, thus improving the ability of the robot to make progress toward its target location in the allotted cycle time for each increment movement. (Moore - ¶7).
While Liu in view of Moore does disclose an obstacle avoidance system utilizing directional vector components (¶115-118 and ¶163-167 – a first component that is parallel to the original movement path and a second component that is perpendicular to the original movement path), it does not explicitly disclose these components as distance components.
However, Beer discloses an object sense and avoid system including calculating distance to objects based on a Manhattan distance metric which calculates distance measures utilizing the absolute differences of the Cartesian coordinates representing the position of the mobile device and the object corresponding to the recited based on the obstacle data, determining a first distance between the obstacle and the target path, and a second distance between the obstacle and a current position of the mobile device, wherein the first distance is perpendicular to the target path, and the second distance is parallel to the target path (¶59); and
The combination of the obstacle avoidance system utilizing directional vector components of Liu in view of Moore with the object sense and avoid system including calculating distance to objects based on a Manhattan distance metric of Beer fully discloses the elements as claimed.
It would have been obvious to one of ordinary skill in the art before the filing date to have combined the obstacle avoidance system utilizing directional vector components of Liu in view of Moore with the object sense and avoid system including calculating distance to objects based on a Manhattan distance metric of Beer in order to reduce the weight and expense of high end processing systems typically utilized for obstacle avoidance systems (Beer - ¶3).
Regarding claims 2, 12, and 20, Liu further discloses obtaining scene data of the moving area collected through one or more sensors of the mobile device (¶59 and ¶65 – image data corresponding to the recited scene data collected through sensors of the moveable device);
performing localization on the mobile device and mapping based on the scene data to obtain a current position of the mobile device and an environment map (¶59 and ¶75-76 – image data is utilized to determine the 3D position of the moveable object on the coordinate system corresponding to the recited obtain a current position of the mobile device and an environment map); and
obtaining the cost map of the moving area based on obstacle information in the environment map (¶75-76 – image data is used to position the moveable device and obstacle positions in the coordinate system corresponding to the recited obtaining the cost map of the moving area based on obstacle information in the environment map), and
determining the target path of the mobile device based on the cost map and the current position (¶75-76 – The series of images that are captured by the onboard camera are thus associated with different positions (e.g., z-positions) of the moveable object (e.g., a UAV) on the moveable object's movement path).
Regarding claims 7 and 17, Liu further discloses determining a first speed component of the mobile device based on a first distance of the current target distance and the maximum limiting speed, wherein the first distance is perpendicular to the target path; determining a second speed component of the mobile device based on a second distance of the current target distance and the maximum limiting speed, wherein the second distance is parallel to the target path; and obtaining the straight-line travelling speed component based on the first speed component and the second speed component (¶14 – initial velocity corresponding to the recited straight line traveling speed component is based on a first component that is parallel to the original movement path corresponding to the recited second speed component and a second component that is perpendicular to the original movement path corresponding to the recited first speed component where each component includes the long-range obstacle criteria require that a distance between the moveable object and the obstacle along the original movement path exceeds a first threshold distance corresponding to the recited respective vectoral distance of the current target distance where the speeds implicitly include the limiting factor of the moveable objects speed capabilities corresponding to the recited maximum limiting speed).
Regarding claims 8 and 18, Liu further discloses control the mobile device to move at the target speed in response to the target speed satisfying a preset speed range (¶46 – execute obstacle avoidance corresponding to the recited control the mobile device to move at the target speed in response to the target speed satisfying the speed capabilities of the moveable device corresponding to the recited satisfying a preset speed range).
Claims 4, 5, 14, 15, and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Liu et al. (US 2019/0265734) in view of Moore et al. (US 2019/0094866) and Beer et al. (US 2019/0250641), as applied to claims 1 and 10 above, further in view of Tanaka (US 2016/0274588).
Regarding claims 4, 14, and 22, Liu further discloses determining a turning angle utilizing the originally plotted points and the determined object positioning (¶121-122 and Fig. 12) but does not explicitly disclose utilizing perpendicular lines to determine the curvature.
However, Tanaka discloses an autonomous vehicle curvature radius calculation system including based on the cost map, determining a first reference line segment and a second reference line segment within a preset range in front of the mobile device, wherein the first reference line segment and the second reference line segment are both perpendicular to the target path, and a preset distance is spaced between the first reference line segment and the second reference line segment; and determining the current turning curvature of the mobile device based on an angle between the first reference line segment and the second reference line segment (¶25-27, ¶108-109, ¶196, and Figs. 9-10 – subgoal points are separated by a predetermined distance corresponding to the recited a preset distance is spaced between the first reference line segment and the second reference line segment where the intersection of the perpendicular bisectors of the subgoal points corresponding to the recited first and second reference line segment are utilized to determine the curvature radius and therefore the turning angle where the points are separated from a current position by a predetermined distance corresponding to the recited within a preset range in front of the mobile device).
The combination of the system and method for object detection and movement adjustment maneuvers utilizing a coordinate system of Liu in view of Moore and Beer with the curvature angle determination system of Tanaka fully discloses the elements as claimed.
It would have been obvious to one of ordinary skill in the art before the filing date to have combined the system and method for object detection and movement adjustment maneuvers utilizing a coordinate system of Liu in view of Moore and Beer with the curvature angle determination system of Tanaka in order to determine the optimal control parameters for autonomous vehicles (Tanaka - ¶217).
Regarding claims 5 and 15, Liu further discloses determining a turning angle utilizing the originally plotted points and the determined object positioning (¶121-122 and Fig. 12) but does not explicitly disclose utilizing perpendicular lines to determine the curvature.
However, Tanaka further discloses in response to the first reference line segment intersecting with the second reference line segment, determining intersection coordinates of the first reference line segment and the second reference line segment based on the cost map, determining the angle between the first reference line segment and the second reference line segment based on the intersection coordinates and the preset distance, and determining the angle as the current turning curvature; or in response to the first reference line segment not intersecting with the second reference line segment, determining that the current turning curvature is zero (¶25-27, ¶108-109, ¶196, and Figs. 9-10 – subgoal points are separated by a predetermined distance corresponding to the recited a preset distance is spaced between the first reference line segment and the second reference line segment where the intersection of the perpendicular bisectors of the subgoal points corresponding to the recited first and second reference line segment are utilized to determine the curvature radius and therefore the turning angle where the points are separated from a current position by a predetermined distance corresponding to the recited within a preset range in front of the mobile device. The claim element “or” only requires one of the group to be included to disclose the entirety of the claim as written).
The combination of the system and method for object detection and movement adjustment maneuvers utilizing a coordinate system of Liu in view of Moore and Beer with the curvature angle determination system of Tanaka fully discloses the elements as claimed.
It would have been obvious to one of ordinary skill in the art before the filing date to have combined the system and method for object detection and movement adjustment maneuvers utilizing a coordinate system of Liu in view of Moore and Beer with the curvature angle determination system of Tanaka in order to determine the optimal control parameters for autonomous vehicles (Tanaka - ¶217).
Additional References Cited
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Bonarens et al (US 2017/0186322) discloses an obstacle avoidance system including utilizing a) a component of a candidate trajectory extending parallel to the roadway is defined by selecting weighting coefficients of a first weighted sum of orthogonal functions of the time, b) a component of the candidate trajectory extending perpendicular to the roadway is defined by selecting weighting coefficients of a second weighted sum of the orthogonal functions, c) an optimization parameter for the candidate trajectory is calculated, and d) at least one coefficient of at least one of the sums is varied and step c) is repeated if the optimization parameter does not reach a stop criterion (¶5).
Bruno et al. (US 2022/0355820) discloses an obstacle avoidance system including utilizing a minimum safety distance dmin which is oriented with respect to the vehicle and therefore with respect to the obstacle, such that said distance has a longitudinal component along the X-axis and a lateral component along the Y-axis (¶105).
Conclusion
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/MATTHEW J. REDA/ Primary Examiner, Art Unit 3665