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 1-20 are pending and examined below. This action is in response to the claims filed 1/19/26.
Response to Amendment
Applicant’s arguments, see Applicant Remarks Claim Objection filed on 1/19/26, regarding Claim Objections are persuasive in view of amendments filed 1/19/26. Claim Objections are withdrawn.
Applicant’s arguments, see Applicant Remarks 35 USC § 102 and 35 USC § 103 filed on 1/19/26, regarding 35 USC § 102 and 35 USC § 103 rejections have been fully considered and are not found persuasive.
Regarding applicants remarks, pages 9-10, asserts the following:
“generating a first obstacle avoidance path with a first parameter based on a characteristic information of the obstacle, and controlling the mowing robot to operate based on the first obstacle avoidance path, the characteristic information of the obstacle at least include the horizontal width of the obstacle, the first obstacle avoidance path is a first non-linear line configured to get around the obstacle; generating a second obstacle avoidance path with a second parameter, when the obstacle is detected again in the first obstacle path; updating the characteristic information of the obstacle; determining the second parameter based on an updated characteristic information of the obstacle, generating the second obstacle avoidance path based on the second parameter, the second obstacle avoidance path is a second non-linear line configured to get around the obstacle, the second non-linear line is longer than the first non-linear line.
The Examiner asserts that Kulkarni discloses the features of claim 1. Specifically, according to Kulkarni, paragraph [0231] recites that permanent obstacle avoidance can be iterative, such that obstacles may be avoided by running the electronic device along the planned path multiple times until a stable map is obtained. Based on the foregoing disclosure, the Examiner concludes that Kulkarni teaches the "second obstacle avoidance path" of the present application.
Applicant respectfully disagrees with the Examiner's position that Kulkarni discloses the claimed "second obstacle avoidance path," for at least the following reasons.
First, paragraph [0231] of Kulkarni states that "the permanent obstacle avoidance can be iterative to avoid obstacles by running the electronic device on the planned path multiple times until a stable map is obtained." This disclosure indicates that the electronic device performs the operation multiple times, and during such multiple runs, the device may encounter the obstacle repeatedly.
However, Kulkarni's iterative concept is directed to repeating the overall task/path planning operation in order to build a stable map and ultimately classify an obstacle as a permanent obstacle, rather than dynamically generating multiple distinct avoidance paths within a single obstacle avoidance process as recited in the present claims.
Specifically, as shown in FIG. 11H and described in paragraph [0232] of Kulkarni, the electronic device 210 obtains the previously generated boundary mapping and then plans a path inside the obtained boundary. In step 1142, the electronic device 210 traverses the planned path.
In step 1143, the electronic device 210 determines whether an obstacle is detected. When an obstacle is not detected, the electronic device 210, in step 1146, continues on its planned path. When an obstacle is detected, the electronic device 210, in step 1144, follows the boundary of the obstacle while mapping it in the grid map. the electronic device 210 can follow the obstacle using the process described above in FIG. 11G. After following the boundary of the obstacle, the electronic device 210, in step 1145, replaces a path from its current location to the finish point. The electronic device 210 the continues on the re-planned path in step 1146.
Accordingly, Kulkarni at most discloses that, upon detecting an obstacle, the device re-plans a path from its current location to the finish point during a single traversal. Such re-planning is essentially equivalent to Applicant's claimed first obstacle avoidance path, and cannot reasonably be equated to the claimed second obstacle avoidance path.
In fact, Kulkarni's "iterative" permanent obstacle avoidance is achieved only after multiple task executions, where the electronic device repeatedly detects an obstacle at the same position and then marks the obstacle as a permanent obstacle. Kulkarni therefore fails to disclose or suggest that, during obstacle avoidance, the device would update characteristics of the obstacle based on detecting the obstacle again in the first obstacle avoidance path, and then generate a second obstacle avoidance path based on the updated obstacle characteristics, as expressly required by the present claims.
Therefore, Kulkarni does not teach the claimed "second obstacle avoidance path," and the Examiner's reliance on paragraph [0231] is misplaced.”
Regarding applicant’s assertion that Kulkarni “fails to disclose or suggest that, during obstacle avoidance, the device would update characteristics of the obstacle based on detecting the obstacle again in the first obstacle avoidance path, and then generate a second obstacle avoidance path based on the updated obstacle characteristics, as expressly required by the present claims” the applicant admits that Kulkarni does disclose repeatedly detecting an obstacle at the same position and updating the characteristics of the obstacle while performing obstacle avoidance during obtaining of a stable map.
It appears that the contention lies within normal operation obstacle avoidance as opposed to during a training phase and the establishment of a stable map. However, Kulkarni further discloses utilizing the same obstacle avoidance techniques to avoid obstacles not identified during the training phase as well as dynamic obstacles, where it first waits to see if the obstacle moves and if it doesn’t it replans the path to avoid the obstacle as disclosed in more detail during the training phase and cited in the rejection below. (Kulkarni - ¶151-156 and Fig. 6C).
Kulkarni’s iterative approach during the training phase best explains the technique for obstacle avoidance, however the system further performs the same mapping/path planning system during normal operations to determine if there is a new permeant obstacle or if there any other detected obstacle blocking the path.
Therefore, unless further distinguishing features are explicitly claimed, Kulkarni does disclose the claims as written.
Regarding applicants remarks, pages 11-13, asserts the following:
Applicant further respectfully traverses the Examiner's reliance on Kulkarni as allegedly teaching the claimed "second obstacle avoidance path."
As described in Kulkarni (see, e.g., FIG. 11I), upon detecting an obstacle, the electronic device follows the boundary of the obstacle and then replans a path from the current location to the finish point. In other words, Kulkarni's approach does not generate a planned obstacle avoidance path in advance. Rather, Kulkarni performs a boundary-following maneuver that is effectively a reactive and exploratory avoidance behavior, and only thereafter generates a replacement path from the current location to the finish point.
Accordingly, Kulkarni does not teach or suggest generating multiple distinct obstacle avoidance paths based on obstacle characteristics, nor does Kulkarni disclose updating obstacle characteristic information upon detecting the obstacle again in a first obstacle avoidance path.
In particular, Kulkarni fails to disclose the claimed sequence of features, including generating a second obstacle avoidance path with a second parameter, when the obstacle is detected again in the first obstacle path; updating the characteristic information of the obstacle; determining the second parameter based on an updated characteristic information of the obstacle, generating the second obstacle avoidance path based on the second parameter, the second obstacle avoidance path is a second non-linear line configured to get around the obstacle, the second non-linear line is longer than the first non-linear line."
In the present application, the amended claim includes the limitation that "the characteristic information of the obstacle at least includes the horizontal width of the obstacle, the first obstacle avoidance path is a non-linear line to get round the obstacle." This means that the obstacle avoidance path is generated at least based on the width of the obstacle, and the robot determines the first obstacle avoidance path by using such width information. Moreover, the first obstacle avoidance path is expressly defined as a non-linear detour path designed to bypass the obstacle. Both the first obstacle avoidance path and the second obstacle avoidance path are thus explicitly planned detour paths, which bypass the obstacle by applying different parameters.
Further, the amended claim 1 also recites that "after the obstacle is detected again in the first obstacle avoidance path, the method further comprises: updating the characteristic information of the obstacle; determining the second parameter based on the updated characteristic information of the obstacle; generating the second obstacle avoidance path based on the second parameter;
wherein a starting point and an ending point corresponding to the first obstacle avoidance path and the second obstacle avoidance path are located in the travel path, the second non-linear line is longer than the first non-linear line ."
Thus, claim 1 requires two explicitly planned detour paths (a first non-linear line and a second non-linear line), generated using different parameters, with the second detour path being generated after the obstacle is detected again during execution of the first detour path, and with the second detour path being longer than the first.
Accordingly, the approach disclosed in the present application is fundamentally different from that of Kulkarni. Kulkarni's disclosure is directed to identifying a permanent obstacle through multiple runs until a stable map is obtained. In contrast, the present application is directed to adaptive, multi-stage obstacle avoidance path generation, specifically designed to dynamically get around persistent obstacles by generating a refined detour path based on updated obstacle characteristic information.
Regarding applicant’s assertion that “Kulkarni does not teach or suggest generating multiple distinct obstacle avoidance paths based on obstacle characteristics, nor does Kulkarni disclose updating obstacle characteristic information upon detecting the obstacle again in a first obstacle avoidance path”, the first obstacle avoidance path includes the first attempt at avoiding an obstacle based on following the boundary of the obstacle at step 1135 of Kulkarni.
See the annotated Figures of Kulkarni below:
PNG
media_image1.png
382
522
media_image1.png
Greyscale
Fig. 11G annotated (a)
During the first obstacle avoidance path, where the path follows the boundary of the obstacle during an iterative approach, the initial obstacle avoidance path only can utilize the data available from gathered sensor data, therefore without knowing the full dimensions of the obstacle, the first obstacle avoidance path planned utilizing the initial sensor data determining the presence of an unknown obstacle does not fully complete connection back to the original path before observing the full obstacle.
PNG
media_image2.png
364
612
media_image2.png
Greyscale
Fig. 11G annotated (b)
The second obstacle avoidance path is generated upon having additional information about the obstacle including the sizing and positioning information not initially determined when planning the first obstacle avoidance path with the initial observation of the obstacle corresponding to the recited first parameter based on a characteristic information of the obstacle, therefore generating a second obstacle avoidance path utilizing an iterative observation and avoidance route by following the boundaries of the area as well as the boundaries of the unknown obstacle as it is observed corresponding to the recited second parameter being greater than the first parameter since it includes more information about the border of the obstacle, therefore including the second obstacle avoidance path being longer than the first, both of which are non-linear and attempting to reach the goal, therefore starting and ending on the travel path.
Therefore, the rejections are maintained.
Regarding applicants remarks, pages 13-14, asserting the following:
Connell discloses a mobile robot operating in an indoor environment, systematically visiting tiles in a space for the purpose of detecting energy and environmental leaks (see steps 404-428).When the robot reaches a dead-end, meaning it has no unvisited adjacent tiles, it backs up to a previous tile that offers unvisited neighbors, continuing this process until all tiles have been visited. Ultimately, if no new tiles remain, the robot returns to the very first tile, marking the end of traversal.
Critically, Connell's approach centers on environmental coverage and tile-by-tile exploration, with no teaching or suggestion of dynamic obstacle avoidance or updating obstacle characteristics to generate a refined path. The robot in Connell does not generate an alternative obstacle avoidance path, nor does it modify path-planning behavior based on learned or updated information about an obstacle.
Applicant acknowledges that Connell discloses, in order to ensure all tiles are visited, when the robot reaches a dead end and cannot access a new unvisited tile, the robot may back up until it detects a tile with unvisited neighbors. As Connell discloses, in such a dead-end situation, the robot repeatedly attempts movement. Applicant further acknowledges that Connell has disclosed repeated attempts in this limited context.
However, the Examiner must also recognize that Connell's motivation for repeated attempts lies in ensuring complete tile coverage, rather than avoiding obstacles. By contrast, Kulkarni relates to obstacle avoidance when the robot encounters an obstacle, and at most involves a "wait- and-single-reroute" strategy. Kulkarni neither discloses nor suggests a "multi-stage obstacle avoidance path generation based on obstacle characteristic parameters.", Connell's goal is complete indoor coverage traversal.
Even if Kulkarni, and Connell were combined, the resulting system would, at best, under the technical suggestion of Connell, Connell contributes only a concept of repeated attempts, but strictly in the context of indoor tile-based exploration to ensure full coverage, and does not involve updating obstacle parameters, and not refer to the second avoidance path longer than the first avoidance path.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
Regarding the applicant’s assertion that the combination of Kulkarni in view of Connell “would, at best, under the technical suggestion of Connell, Connell contributes only a concept of repeated attempts, but strictly in the context of indoor tile-based exploration to ensure full coverage, and does not involve updating obstacle parameters, and not refer to the second avoidance path longer than the first avoidance path”, both Kulkarni and Connel as well as the claimed invention of the present application disclose a system for autonomously navigating in an environment with unknown variables as well as recording updated information about the environment throughout the vehicle movement.
All of the above systems utilize bounded area in an area reconstructed utilizing sensor data observed during movement to record and update the most accurate depiction of surroundings for safely and efficiently navigating through an environment while avoiding obstacles (Zhang - ¶39 and ¶46-47; Kulkarni - ¶149-156; Connell - ¶36-37).
To reduce each reference to individual parts of a singular embodiment is not considering either of the art in their entirety or the combination as explicitly detailed in the Non-Final Rejection of 10/20/25. All of the systems are attempting to navigate in an environment with unknowns while recording new updated information throughout autonomous navigation and obstacle avoidance movements. The combination of the obstacle avoidance routing of Kulkarni with the mapping and routing at dead ends to return to the starting point of Connell does fully disclose 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 routing of Kulkarni with the mapping and routing at a dead end of Connell in order to accurately analyze the boundaries of a mobile robot pathing/mapping system (Connell - ¶59).
Therefore, a person of ordinary skill in the art would have been motivated to combine the prior art to achieve the claimed invention and whether there would have been a reasonable expectation of success in doing so.
Therefore the rejections are maintained.
Applicant’s remarks, page 14 further asserts;
The most likely outcome of combining these three references is a system in which the robot directly obtains an avoidance path based on obstacle recognition. However, because Ebrahimi already provides precise obstacle size and type, such a system would simply yield a direct obstacle avoidance path. In contrast, the present application requires multi-stage avoidance paths generated based on updated obstacle parameters. Furthermore, unlike the indoor environment in Connell where dead-end conditions exist and motivate repeated attempts, the mowing environment is an open lawn area. In such an environment, if Kulkarni's robot were to randomly navigate unvisited regions without multi-stage path refinement, the mowing path would become disordered and uncontrollable.
Regarding applicant’s above assertion, there is no recitation within the rejection of a combination of Kulkarni in view of Connell and Ebrahimi, therefore there is no current reason to consider the combination of all three together. Should the claims relying upon the different dependent rejections be rewritten to include subject matter rejected by all three references then the combination of the three will be considered as to the validity and motivation to combine. As such combination is not currently claimed, it is not considered.
Therefore the rejections are maintained.
Applicant’s remarks, page 14, regarding Dependent Claims and Closing presents no new arguments instead relying upon the persuasiveness of the above arguments.
Therefore the rejections are maintained.
Rejections are updated to address claim amendments below.
The office advises the utilization of interviews in the process of creating the most efficient and constructive examination process in that the interpretations of the examiner and applicant of both the art of record as well as the present application are expressed in a mutual agreement in order to create and push forward the most productive discussions/amendments to move towards allowance.
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 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.
(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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-5, 9-13, and 17-20 are rejected under 35 U.S.C. 102(a)(1) and (a)(2) as being anticipated by Kulkarni et al. (US 2021/0064043).
Regarding claims 1, 9, and 17, Kulkarni discloses an automatic lawn mower with obstacle avoidance including a mowing robot, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the program, when executed by the processor, causes the processor to perform an intelligent obstacle avoidance method, the intelligent obstacle avoidance method comprising (¶55 and ¶63):
detecting an obstacle in a travel path of an autonomous robot (¶156 and Fig. 6C – element 614);
generating a first obstacle avoidance path with a first parameter based on a characteristic information of the obstacle, and controlling the mowing robot to operate based on the first obstacle avoidance path, the characteristic information of the obstacle at least include the horizontal width of the obstacle, the first obstacle avoidance path is a first non-linear line configured to get around the obstacle (¶224-233 and Fig. 11A-K – when an obstacle is initially detected, the device follows the initially detected boundary of the obstacle corresponding to the recited first obstacle avoidance path based on initially detected position information of the obstacle corresponding to the recited characteristic information including the avoidance route around the obstacle corresponding to the recited first parameter, where the position information is mapped onto the grid map including all birds eye 2D dimensions of the object therefore including the horizontal width of the obstacle as seen in Fig. 11G including the path being non-linear);
[AltContent: rect][AltContent: oval][AltContent: ]
PNG
media_image1.png
382
522
media_image1.png
Greyscale
Fig. 11G annotated (a)
generating a second obstacle avoidance path with a second parameter, when the obstacle is detected again in the first obstacle path; controlling the mowing robot to operate based on the second obstacle avoidance path, the second parameter being greater than the first parameter, the second obstacle avoidance path is a non-linear line configured to get around the obstacle (¶224-233 and Fig. 11A-K – the permanent obstacle avoidance can be iterative to avoid obstacles by running the electronic device on the planned path multiple times until a stable map is obtained corresponding to the recited second obstacle avoidance path when the obstacle is detected again in the first obstacle avoidance path. The following of the boundary of an obstacle repeatedly moves along the obstacle until it no longer detects the obstacle within the path therefore iteratively generating new obstacle avoidance paths until it is no longer detected corresponding to the recited second obstacle avoidance path including the avoidance route around the obstacle corresponding to the recited second parameter since the longer the perimeter of the object the longer the deviation route corresponding to the recited second parameter being greater than the first parameter where Fig. 11G shows the path is non-linear); and
PNG
media_image2.png
364
612
media_image2.png
Greyscale
Fig. 11G annotated (b)
adjusting a parameters of path generation until the obstacles in the travel path are bypassed (¶224-233 and Fig. 11A-K – the permanent obstacle avoidance can be iterative to avoid obstacles by running the electronic device on the planned path multiple times until a stable map is obtained where the parameters are adjusted continually until the object is passed);
wherein after the obstacle is detected again in the first obstacle avoidance path, the method further comprises (¶224-233 and Fig. 11A-K – the permanent obstacle avoidance can be iterative to avoid obstacles by running the electronic device on the planned path multiple times until a stable map is obtained where the parameters are adjusted continually until the object is passed):
updating the characteristic information of the obstacle (¶224-233 and Fig. 11A-K – the position of the object is mapped onto the grid map as it is continuously detected along its border corresponding to the recited updating the characteristic information of the obstacle);
determining the second parameter based on an updated characteristic information of the obstacle, generating the second obstacle avoidance path based on the second parameter, the second obstacle avoidance path is a second non-linear line configured to get around the obstacle, the second non-linear line is longer than the first non-linear line (¶224-233 and Fig. 11A-K – determining the extension of the obstacle avoidance path based on the continued detection of the border of the obstacle using additionally observed information of the obstacle after the initial observation corresponding to the recited determining the second parameter based on an updated characteristic information of the obstacle and generating the second obstacle avoidance path based on the second parameter where the additionally determined obstacle sizing/position information requires further routing longer than the obstacle, see Fig. 11G annotated (a) and Fig. 11G annotated (b) above);
a starting point and an ending point corresponding to the first obstacle avoidance path and the second obstacle avoidance path are located on the travel path (¶224-233 and Fig. 11A-K – upon detection of the obstacle, following the boundary of the obstacle until motion on the original path can be resumed corresponding to the recited starting and ending point corresponding to the recited first and second obstacle avoidance paths being on the travel path).
Regarding claims 2, 10, and 18, Kulkarni further discloses the generating the first obstacle avoidance path with the first parameter based on the characteristic information of the obstacle comprises: obtaining characteristic information of the obstacle; and calculating the first parameter based on the characteristic information of the obstacle, and generating the first obstacle avoidance path along a current mowing direction with the first parameter (¶224-233 and Fig. 11A-K – when an obstacle is detected, the device follows the boundary of the obstacle along a mowing path corresponding to the recited first obstacle avoidance path based on detected position information of the obstacle corresponding to the recited characteristic information including the avoidance route around the obstacle corresponding to the recited first parameter, where the position information is mapped onto the grid map including all birds eye 2D dimensions of the object therefore including the horizontal width of the obstacle as seen in Fig. 11G).
Regarding claims 3, 11, and 19, Kulkarni further discloses the calculating the first parameter based on the characteristic information of the obstacle, and generating the first obstacle avoidance path along a current mowing direction with the first parameter comprises: the characteristic information of the obstacle comprises a horizontal width of the obstacle; calculating a first length range based on the horizontal width of the obstacle, and generating the first obstacle avoidance path along the current mowing direction that satisfies the first length range (¶224-233 and Fig. 11A-K – when an obstacle is detected, the device follows the boundary of the obstacle corresponding to the recited first obstacle avoidance path based on detected position information of the obstacle corresponding to the recited characteristic information including the avoidance route around the obstacle corresponding to the recited first parameter, where the position information is mapped onto the grid map including all birds eye 2D dimensions of the object therefore including the horizontal width and length range of the obstacle as seen in Fig. 11G).
Regarding claims 4, 12, and 20, Kulkarni further discloses the generating the first obstacle avoidance path along the current mowing direction that satisfies the first length range comprises: determining a side length parameter based on the first length range, and generating a first polyline path along the current mowing direction with the side length parameter (¶224-233 and Fig. 11A-K – when an obstacle is detected, the device follows the boundary of the obstacle corresponding to the recited first obstacle avoidance path along the current mowing direction that satisfies the first length range by generating a first polyline path based on detected position information of the obstacle corresponding to the recited characteristic information including the avoidance route around the obstacle corresponding to the recited first parameter, where the position information is mapped onto the grid map including all birds eye 2D dimensions of the object therefore including the horizontal width and length range of the obstacle as seen in Fig. 11G).
Regarding claims 5 and 13, Kulkarni further discloses the generating the first obstacle avoidance path along the current mowing direction that satisfies the first length range comprises: determining an arc angle parameter and an arc length parameter based on the first length range, and generating a first arc path along the current mowing direction with the arc angle parameter and the arc length parameter (¶224-233 and Fig. 11A-K – when an obstacle is detected, the device follows the boundary of the obstacle corresponding to the recited first obstacle avoidance path along the current mowing direction that satisfies the first length range by generating a first polyline path based on detected position information of the obstacle corresponding to the recited characteristic information including the avoidance route around the obstacle corresponding to the recited first parameter, where the position information is mapped onto the grid map including all birds eye 2D dimensions of the object therefore including the horizontal width and length range of the obstacle as seen in Fig. 11G where the boundary of the obstacle is the arc angle parameter and arc length parameter generated from the mapped boundary of the obstacle which includes the first length range).
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 6 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Kulkarni et al. (US 2021/0064043), as applied to claims 2 and 12 above, in view of Connell, II et al. (US 2012/0078417), herein “Connell”.
Regarding claims 6 and 14, Kulkarni further discloses the generating the second obstacle avoidance path with the second parameter, and controlling the mowing robot to operate based on the second obstacle avoidance path comprises (¶224-233 and Fig. 11A-K – the permanent obstacle avoidance can be iterative to avoid obstacles by running the electronic device on the planned path multiple times until a stable map is obtained corresponding to the recited second obstacle avoidance path when the obstacle is detected again in the first obstacle avoidance path. The following of the boundary of an obstacle repeatedly moves along the obstacle until it no longer detects the obstacle within the path therefore iteratively generating new obstacle avoidance paths until it is no longer detected corresponding to the recited second obstacle avoidance path):
updating the characteristic information of the obstacle (¶224-233 and Fig. 11A-K – the position of the object is mapped onto the grid map as it is continuously detected along its border corresponding to the recited updating the characteristic information of the obstacle);
determining the second parameter with an updated characteristic information, and generating the second obstacle avoidance path based on the second parameter (¶224-233 and Fig. 11A-K – determining the extension of the obstacle avoidance path based on the continued detection of the border of the obstacle corresponding to the recited determining the second parameter based on an updated characteristic information of the obstacle and generating the second obstacle avoidance path based on the second parameter); and
Kulkarni does not explicitly disclose returning to a starting point, however Connell discloses a mobile robot detection system including controlling the mowing robot to return to a starting point of the first obstacle avoidance path, and controlling the mowing robot to operate based on the second obstacle avoidance path (¶71 – backing up until the robot detects unvisited neighbor tiles corresponding to the recited returning to a starting point of the first path where it continues to new tiles corresponding to the recited second path).
The combination of the obstacle avoidance routing of Kulkarni with the mapping and routing at a dead end of Connell 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 routing of Kulkarni with the mapping and routing at a dead end of Connell in order to accurately analyze the boundaries of a mobile robot pathing/mapping system (Connell - ¶59).
Claims 7 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Kulkarni et al. (US 2021/0064043), as applied to claims 1 and 9 above, in view of Dalfra et al. (US 2020/0201347).
Regarding claims 7 and 15, Kulkarni further discloses the generating the first obstacle avoidance path with the first parameter based on the detection result comprises (¶224-233 and Fig. 11A-K – when an obstacle is detected, the device follows the boundary of the obstacle corresponding to the recited first obstacle avoidance path based on detected position information of the obstacle corresponding to the recited characteristic information including the avoidance route around the obstacle corresponding to the recited first parameter):
Kulkarni does not disclose utilizing an angle of the object to determine the angle to go around it, however, Dalfra discloses an obstacle avoidance method for robots including dividing a horizontal angle of the obstacle into a left deflection angle and a right deflection angle along an orientation of the mowing robot (¶388-389 – determining the direction at which the obstacle is identified as left or right corresponding to the recited left deflection angle or right deflection angle);
comparing the left deflection angle with the right deflection angles to determine a deflection direction (¶388-389 - determining which side of the lawn mower the object is on corresponding to the recited determining a deflection direction); and
generating the first obstacle avoidance path based on the deflection direction and the first parameter (¶388-389 – determining an obstacle avoidance trajectory based on the side of the mower the object is on corresponding to the recited deflection direction).
The combination of the obstacle avoidance system of Kulkarni with the directional avoidance path planning of Dalfra 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 of Kulkarni with the directional avoidance path planning of Dalfra in order to improve the efficiency of obstacle avoidance (Dalfra - ¶389).
Claims 8 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Kulkarni et al. (US 2021/0064043), as applied to claims 1 and 9 above, in view of Izumikawa et al. (US 11,148,593).
Regarding claims 8 and 16, Kulkarni does not explicitly disclose obtaining a number of times the obstacle is detected again however Izumikawa discloses an automated safety alert for a machine environment including obtaining a number of times the obstacle is detected again in the first obstacle avoidance path; and generating warning information to prompt a user when the number of times exceeds a preset number of times (Col 18:50-19:46 – number of times a person is detected in a predetermined area at an alarm level corresponding to the recited preset number of times generates an alarm to the operator corresponding to the recited prompting the user).
The combination of the obstacle avoidance routing system of Kulkarni with the human monitoring safety level alerts of Izumikawa 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 routing system of Kulkarni with the human monitoring safety level alerts of Izumikawa in order to ensure the safety of the work site (Izumikawa – Col 19:40-46).
Additional References Cited
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Dalfra et al. (US 2020/0201347) discloses a self-moving device including obstacle avoidance where the device adjusts steering angles repeatedly to slowly adjust the steering angle such that an obstacle is not in the moving direction of the device but moves along it until the obstacle is avoided (¶657-658).
Kuroda (US 2008/0269973) discloses a routing apparatus for an autonomous mobile unit including obstacle avoidance with an initial path utilizing relevant information in its initial field of view then readjusting the path based on detecting additional obstacle presence within the first adjusted route requiring a secondary adjustment of the route (¶51-53).
Conclusion
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 Matthew J Reda whose telephone number is (408)918-7573. The examiner can normally be reached Monday - Friday 7-4 ET.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Hunter Lonsberry can be reached at (571) 272-7298. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MATTHEW J. REDA/ Primary Examiner, Art Unit 3665