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 .
Status of Claims
This action is in reply to the amendment filed on 28 April 2026.
Claim(s) 1-26 are currently pending and have been examined.
This action is made FINAL.
Response to Arguments/Amendments
Applicant's arguments with respect to the objections to the claims have been fully considered and are persuasive. The objection to claim(s) 12-13 has been withdrawn.
Applicant's arguments with respect to the rejection of claim(s) 1-26 under 35 U.S.C. 112(b) have been fully considered and are persuasive. The rejection of claim(s) 1-26 under 35 U.S.C. 112(b) has been withdrawn.
Applicant's arguments, see remarks at page(s) 9-12, filed 28 April 2026, with respect to the rejection of claim(s) 1-26 under 35 U.S.C. 102 and/or 103 over Jeong have been fully considered and are persuasive. The Applicant’s amendments overcome the previous art of record. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made over Jeong (US 20250172943 A1) in view of Cha et al. (US 11210533 B1) in further view of Xu et al. (CN 116513172 A).
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 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.
Claim(s) 1-4, 10-11, 14-17 and 23-24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jeong (US 20250172943 A1) in view of Cha et al. (US 11210533 B1) in further view of Xu et al. (CN 116513172 A).
Regarding claims 1 and 14, Jeong teaches a robot control apparatus (abstract “robot”), comprising: a sensor (¶[0045] “sensor module”); at least one processor (¶[0057] “processor”); and a storage medium storing computer-readable instructions (¶[0057] “memory”) that, when executed by the at least one processor, enable the at least one processor to: determine whether an external object and a robot will collide with each other in a first path including a target point, based on identifying the external object using the sensor, while operating the robot along the first path (abstract and ¶[0012] “specific optimal path for moving to a target point” “when the serving robot recognizes an obstacle while moving to the target point… move to the target point through an avoidance path”), wherein the first path is a shortest distance path for causing the robot to move to the target point (¶[0012] “specific optimal path for moving to a target point”; ¶[0074] “shortest path”).
Jeong does not explicitly teach predict a movement path of the external object based on at least one of a speed of the external object or a movement direction of the external object, expand a size of an obstacle box on a map including the first path corresponding to the external object based on a width of the robot, a length of the robot, a width of the obstacle box, and a length of the obstacle box, in response to determining that the robot will collide with the external object along the first path, generate, based on the obstacle box, a second path different than the first path, and operate the robot along the second path for avoiding a collision between the robot and the external object. However, Cha discloses a method of predicting trajectory of a vehicle and teaches predict a movement path of the external object based on at least one of a speed of the external object or a movement direction of the external object (Col. 4, lines 6-37, “predict a trajectory of at least one of the plurality of neighboring vehicles” “moving direction”), in response to determining that the robot will collide with the external object along the first path, generate, based on the obstacle box, a second path different than the first path (Col. 4, line 53-62, “ego vehicle 100 may control the steering, acceleration and/or deceleration of the ego vehicle 100 to safely follow a route or to avoid collision to the first neighboring vehicle”; also, see at least abstract “generating a bounding box associated with the target vehicle, the bounding box surrounding a contour of the target object”), and operate the robot along the second path for avoiding a collision between the robot and the external object (Col. 4, line 53-62, “ego vehicle 100 may control the steering, acceleration and/or deceleration of the ego vehicle 100 to safely follow a route or to avoid collision to the first neighboring vehicle”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method, apparatus and program for obstacle avoidance control of serving robot of Jeong to provide, with a reasonable expectation of success, predict a movement path of the external object based on at least one of a speed of the external object or a movement direction of the external object, in response to determining that the robot will collide with the external object along the first path, generate, based on the obstacle box, a second path different than the first path, and operate the robot along the second path for avoiding a collision between the robot and the external object, as taught by Cha, to provide safely following a route or avoiding collision to neighboring vehicles. (Cha at Col. 4, line 53-62)
The combination of Jeong and Cha does not explicitly teach expand a size of an obstacle box on a map including the first path corresponding to the external object based on a width of the robot, a length of the robot, a width of the obstacle box, and a length of the obstacle box. However, Xu discloses a method for determining vehicle collision risk and teaches expand a size of an obstacle box on a map including the first path corresponding to the external object based on a width of the robot, a length of the robot, a width of the obstacle box, and a length of the obstacle box (page 5 “expansion rule, the length and width of the vehicle rectangle and the obstacle rectangle are expanded to obtain the expanded vehicle rectangle and the expanded obstacle rectangle”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method, apparatus and program for obstacle avoidance control of serving robot of Jeong as modified by Cha to provide, with a reasonable expectation of success, expand a size of an obstacle box on a map including the first path corresponding to the external object based on a width of the robot, a length of the robot, a width of the obstacle box, and a length of the obstacle box, as taught by Xu, to provide improve the safety in the driving process of the intelligent driving vehicle using size information. (Xu at page 10)
Regarding claims 2 and 15, Jeong teaches the apparatus of claim 1, wherein the instructions further enable the at least one processor to determine whether the external object and the robot will collide with each other in the first path, based on information including an identifier assigned to the external object, a type of the external object, a position of the external object, a speed of the external object, or a movement direction of the external object, or any combination thereof (¶[0103]-[0112] “control the serving robot 10 based on the type of obstacle”).
Regarding claims 3 and 16, Jeong teaches the apparatus of claim 1, wherein the instructions further enable the at least one processor to: identify a shortest path for avoiding the external object (¶[0118] “generate the avoidance path using the shortest path calculation algorithm” and ¶[0124] “controlling the serving robot to move to the target point through a newly generated avoidance path”), based on predicting a movement path of the external object (¶[0093] “computing device 100 may recognize the movement paths of other serving robots”); and generate the second path corresponding to the shortest path (¶[0118] “generate the avoidance path using the shortest path calculation algorithm”).
Regarding claims 4 and 17, Jeong teaches the apparatus of claim 1, wherein the instructions further enable the at least one processor to generate the first path, the second path, or the first path and the second path, based on a path algorithm (¶[0118] “generate the avoidance path using the shortest path calculation algorithm”) including a grid-based algorithm, a graph-based algorithm, or a sampling-based algorithm, or any combination thereof (¶[0074] “graph search algorithm”).
Regarding claims 10 and 23, Jeong teaches the apparatus of claim 1, wherein the sensor includes a camera, a light detection and ranging (LiDAR) device, a radio detecting and ranging (RADAR) device, or an obstacle detection sensor, or any combination thereof (¶[0046] “camera”).
Regarding claims 11 and 24, Jeong teaches the apparatus of claim 1, wherein the external object includes a dynamic obstacle (¶[0093] “movement path of other serving robots” or ¶[0110] “recognize an obstacle as a person when there is movement in the obstacle”).
Claim(s) 5 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jeong (US 20250172943 A1) in view of Cha et al. (US 11210533 B1) in view of Xu et al. (CN 116513172 A), as applied to claims 1 and 14 above, and in further view of Wang et al. (US 20200125116 A1).
Regarding claims 5 and 18, the combination of Jeong, Cha and Xu does not explicitly teach the apparatus of claim 1, wherein the instructions further enable the at least one processor to: segment the movement path of the external object into first sections over a designated time, on the map including the first path; segment the first path into second sections over the designated time, based on a speed of the robot; and predict the collision between the external object and the robot, based on that at least one of the first sections and at least one of the second sections overlap with each other. However, Wang discloses a movement control method and system for multiple robots and teaches the apparatus of claim 1, wherein the instructions further enable the at least one processor to: segment the movement path of the external object into first sections over a designated time, on the map including the first path (¶[0022] “task map” “each robot 120a-120n can determine the corresponding predicted moving path according to the received task region and generate corresponding prediction time of each position in the predicted moving path” “segments”); segment the first path into second sections over the designated time, based on a speed of the robot (¶[0022] “task map” “each robot 120a-120n can determine the corresponding predicted moving path according to the received task region and generate corresponding prediction time of each position in the predicted moving path” “segments”; ¶[0028] “speed of the robot”); and predict the collision between the external object and the robot, based on that at least one of the first sections and at least one of the second sections overlap with each other (¶[0022] “task map” “each robot 120a-120n can determine the corresponding predicted moving path according to the received task region and generate corresponding prediction time of each position in the predicted moving path” and “determine whether the predicted moving paths between robots have overlapping segments”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method, apparatus and program for obstacle avoidance control of serving robot of Jeong as modified by Cha as modified by Xu to provide, with a reasonable expectation of success, wherein the instructions further enable the at least one processor to: segment the movement path of the external object into first sections over a designated time, on the map including the first path; segment the first path into second sections over the designated time, based on a speed of the robot; and predict the collision between the external object and the robot, based on that at least one of the first sections and at least one of the second sections overlap with each other, as taught by Wang, to provide re-determining a new predicted moving path to avoid colliding with another robot. (Wang at ¶[0030])
Claim(s) 6-7, 9, 19-20 and 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jeong (US 20250172943 A1) in view of Cha et al. (US 11210533 B1) in view of Xu et al. (CN 116513172 A) in view of Wang et al. (US 20200125116 A1), as applied to claims 5 and 18 above, and in further view of Kim (US 20240399591 A1).
Regarding claims 6 and 19, the combination of Jeong, Cha, Xu and Wang does not explicitly teach the apparatus of claim 5, wherein the instructions further enable the at least one processor to: generate a transit point to avoid the collision, based on the predicting of the collision; and operate the robot along the second path including the transit point, based on the generating of the second path including the transit point on the second path. However, Kim discloses an autonomous driving robot capable of obstacle avoidance movement and teaches the apparatus of claim 5, wherein the instructions further enable the at least one processor to: generate a transit point to avoid the collision, based on the predicting of the collision (Fig. 10 and ¶[0041]-[0043] “collision avoidance destination point”); and operate the robot along the second path including the transit point, based on the generating of the second path including the transit point on the second path (Fig. 10 and ¶[0041]-[0043] “collision avoidance destination point” “movement of the robot may be based on the avoidance trajectory”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method, apparatus and program for obstacle avoidance control of serving robot of Jeong as modified by Cha as modified by Xu as modified by Wang to provide, with a reasonable expectation of success, wherein the instructions further enable the at least one processor to: generate a transit point to avoid the collision, based on the predicting of the collision; and operate the robot along the second path including the transit point, based on the generating of the second path including the transit point on the second path, as taught by Kim, to provide generating an optimal local route with a small amount of calculation and avoiding an obstacle. (Kim at ¶[0011])
Regarding claims 7 and 20, the combination of Jeong, Cha, Xu and Wang does not explicitly teach generate the transit point for bypassing the obstacle box on the map. However, Kim discloses an autonomous driving robot capable of obstacle avoidance movement and teaches generate the transit point for bypassing the obstacle box on the map (Fig. 10 and ¶[0041]-[0043] “collision avoidance destination point” “movement of the robot may be based on the avoidance trajectory”, i.e., the Examiner notes Jeong discloses avoiding an area for the obstacle and using a transit point could be applied the same way for an area of an obstacle).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method, apparatus and program for obstacle avoidance control of serving robot of Jeong as modified by Cha as modified by Xu as modified by Wang to provide, with a reasonable expectation of success, generating the transit point for bypassing the obstacle box on the map, as taught by Kim, to provide generating an optimal local route with a small amount of calculation and avoiding an obstacle. (Kim at ¶[0011])
Regarding claims 9 and 22, the combination of Jeong, Cha, Xu and Wang does not explicitly teach the apparatus of claim 6, wherein the instructions further enable the at least one processor to generate the second path, based on a first partial path connecting a starting point of the robot and the transit point and a second partial path connecting the transit point and the target point. However, Kim discloses an autonomous driving robot capable of obstacle avoidance movement and teaches the apparatus of claim 6, wherein the instructions further enable the at least one processor to generate the second path, based on a first partial path connecting a starting point of the robot and the transit point and a second partial path connecting the transit point and the target point (see Fig. 10).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method, apparatus and program for obstacle avoidance control of serving robot of Jeong as modified by Cha as modified by Xu as modified by Wang to provide, with a reasonable expectation of success, wherein the instructions further enable the at least one processor to generate the second path, based on a first partial path connecting a starting point of the robot and the transit point and a second partial path connecting the transit point and the target point, as taught by Kim, to provide generating an optimal local route with a small amount of calculation and avoiding an obstacle. (Kim at ¶[0011])
Claim(s) 8 and 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jeong (US 20250172943 A1) in view of Cha et al. (US 11210533 B1) in view of Xu et al. (CN 116513172 A) in view of Wang et al. (US 20200125116 A1) in view of Kim (US 20240399591 A1), as applied to claims 6 and 19 above, and in further view of You (US 20210060780 A1).
Regarding claims 8 and 21, the combination of Jeong, Cha, Xu, Wang and Kim does not explicitly teach the apparatus of claim 6, wherein the instructions further enable the at least one processor to generate the transit point in a second direction opposite to a first direction, wherein the first direction includes a movement direction of the external object. However, You discloses a robot avoidance control method and teaches the apparatus of claim 6, wherein the instructions further enable the at least one processor to generate the transit point in a second direction opposite to a first direction (¶[0037]-[0039] “avoidance movement policy is determined according to the orientation information of the external object” “target direction may be a direction opposite to the direction indicated by the orientation information”), wherein the first direction includes a movement direction of the external object (¶[0037]-[0039] “avoidance movement policy is determined according to the orientation information of the external object”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method, apparatus and program for obstacle avoidance control of serving robot of Jeong as modified by Wang as modified by Cha as modified by Xu as modified by Kim to provide, with a reasonable expectation of success, wherein the instructions further enable the at least one processor to generate the transit point in a second direction opposite to a first direction, wherein the first direction includes a movement direction of the external object, as taught by You, to provide reducing the probability that the speed and/or direction is changed while the robot is moving according to the avoidance route. (You at ¶[0044])
Claim(s) 12-13 and 25-26 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jeong (US 20250172943 A1) in view of Cha et al. (US 11210533 B1) in view of Xu et al. (CN 116513172 A), as applied to claims 1 and 14, and in further view of Wallner (US 11155260 B1).
Regarding claims 12 and 25, the combination of Jeong, Cha and Xu does not explicitly teach the apparatus of claim 1, wherein the instructions further enable the at least one processor to: obtain a collision risk index based on an absolute value of a difference between a first index indicating a first position of the external object at a point where the collision between the robot and the external object is predicted and a second index indicating a second position of the robot at the point where the collision between the robot and the external object is predicted, and obtain the second path based the collision risk index. However, Wallner discloses an autonomous vehicle to assess and score all entities registered by an on-board sensor and teaches the apparatus of claim 1, wherein the instructions further enable the at least one processor to: obtain a collision risk index based on an absolute value of a difference between a first index indicating a first position of the external object at a point where the collision between the robot and the external object is predicted and a second index indicating a second position of the robot at the point where the collision between the robot and the external object is predicted (Col. 2, lines 11-35, “determining the speed, direction and behavior of each of the other road entities; (6) scoring each of the other road entities based upon a collision risk it presents to the host vehicle and ranking the other road entities from a highest risk of collision to a lowest risk of collision”), and obtain the second path based the collision risk index (Col. 2, lines 11-35, “calculating accident avoidance and mitigation actions of the host vehicle and dedicating a greater amount of processor resources to the other road entities based on the rank from the highest risk of collision to the lowest risk of collision”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method, apparatus and program for obstacle avoidance control of serving robot of Jeong as modified by Cha as modified by Xu to provide, with a reasonable expectation of success, wherein the instructions further enable the at least one processor to: obtain a collision risk index based on an absolute value of a difference between a first index indicating a first position of the external object at a point where the collision between the robot and the external object is predicted and a second index indicating a second position of the robot at the point where the collision between the robot and the external object is predicted, and obtain the second path based the collision risk index, as taught by Wallner, to provide dedicating a greater amount of processor resources to the other road entities based on the rank from the highest risk of collision to the lowest risk of collision. (Wallner at Col. 2, lines 31-35)
Regarding claims 13 and 26, the combination of Jeong, Cha and Xu does not explicitly teach the apparatus of claim 12, wherein the instructions further enable the at least one processor to: when the external object is instead a plurality of external objects, select a preferred avoidance object, among the plurality of external objects, being closest to the robot or having a smallest collision risk index among a group of the collision risk index of each of the plurality of external objects, based on predicting multiple collisions between the plurality of external objects and the robot; and generate a third path to avoid the robot colliding with the preferred avoidance object, based on the selecting of the preferred avoidance object. However, Wallner discloses an autonomous vehicle to assess and score all entities registered by an on-board sensor and teaches the apparatus of claim 12, wherein the instructions further enable the at least one processor to: when the external object is instead a plurality of external objects, select a preferred avoidance object, among the plurality of external objects, being closest to the robot or having a smallest collision risk index among a group of the collision risk index of each of the plurality of external objects, based on predicting multiple collisions between the plurality of external objects and the robot (Col. 2, lines 11-35, “determining the speed, direction and behavior of each of the other road entities; (6) scoring each of the other road entities based upon a collision risk it presents to the host vehicle and ranking the other road entities from a highest risk of collision to a lowest risk of collision, and (7) calculating accident avoidance and mitigation actions of the host vehicle and dedicating a greater amount of processor resources to the other road entities based on the rank”, i.e., the higher risk closer objects are going to be dealt with first); and generate a third path to avoid the robot colliding with the preferred avoidance object, based on the selecting of the preferred avoidance object (Col. 2, lines 11-35, “calculating accident avoidance and mitigation actions of the host vehicle and dedicating a greater amount of processor resources to the other road entities based on the rank from the highest risk of collision to the lowest risk of collision”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method, apparatus and program for obstacle avoidance control of serving robot of Jeong as modified by Cha as modified by Xu to provide, with a reasonable expectation of success, wherein the instructions further enable the at least one processor to: wherein when the external object is instead a plurality of external objects, select a preferred avoidance object, among the plurality of external objects, being closest to the robot or having a smallest collision risk index among a group of the collision risk index of each of the plurality of external objects, based on predicting multiple collisions between the plurality of external objects and the robot; and generate a third path to avoid the robot colliding with the preferred avoidance object, based on the selecting of the preferred avoidance object, as taught by Wallner, to provide dedicating a greater amount of processor resources to the other road entities based on the rank from the highest risk of collision to the lowest risk of collision. (Wallner at Col. 2, lines 31-35)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Yadmellat et al. (US 20210064040 A1) is pertinent because it is a system and method for predictive path planning in autonomous vehicles.
THIS ACTION IS MADE FINAL. 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 Connor L Knight whose telephone number is (571)272-5817. The examiner can normally be reached Mon-Fri 8:30AM-4:30PM EST.
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/C.L.K/Examiner, Art Unit 3666
/ANNE MARIE ANTONUCCI/Supervisory Patent Examiner, Art Unit 3666
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