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 .
Continued Examination Under 37 CFR 1.114
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 05/11/2026 has been entered.
Claim(s) 1 4, 9, and 16 have been amended. Claim(s) 2, 5-8, 10-15, and 17-18 have been cancelled. Claim(s) 21-23 have been added. Claim(s) 1, 3-4, 9, 16, and 19-23 are pending examination. In response to the instant amendment the claim objects to claims 14 and 16 are removed. This action is made non-final.
Response to Arguments
Applicant presents the following argument(s) regarding the previous office action:
Applicant asserts that the 35 USC 103 rejections of independent claims 1 and 9 is improper because the cited prior art fails to teach all claim limitations as taught/amended. Specifically applicant alleges that Braidic and Attar fail to teach “wherein the task comprises performing the target operation along an edge of the target water region and performing the target operation in the target water region along a planned route; after it is determined that the pool robot completes the task, controlling the pool robot to perform a patrolling operation in the target water region.”
Applicant asserts that the 35 USC 103 rejection of independent claims 1 and 9 is improper. Applicant alleges that Braidic fails to teach the limitation of “wherein the pool robot operates along the fixed route, determining a target position of a target object if the analysis result indicates that there is the target object in the target water region, and controlling the pool robot to directly move to the target position and perform a target operation corresponding to a type of the target object.”
Applicant's arguments filed 05/11/2026 have been fully considered but they are not persuasive.
Regarding applicant’s argument A, the examiner respectfully disagrees. Applicant's arguments fail to comply with 37 CFR 1.111(b) because they amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references. Applicant’s arguments regarding the claimed limitation amount to pointing out how their method would be an improvement over the prior art, but provides no reasoning and/or rationale for this to be the case. Applicant broadly points to the cited portions of Attar, that they feel they overcome, and provides a general assertion of what is taught but provides no actual text from Attar, nor any articulated reasoning of how the claims over Attar that cannot be boiled down to a mere allegation. Accordingly, the examiner is not persuaded by this argument.
Regarding applicant’s argument B, the examiner respectfully disagrees. In light of the amendment the applicant asserts that Braidic does not move along a fixed route and move directly to the target object. However, looking at Braidic [0070] it is taught that, “the control algorithm may determine a singular pathway for removing the candidate debris from the aquatic environment. As noted above, the controller 102 will then navigate the pool cleaner 20 along the pathway until the aquatic environment is clean (all candidate debris is removed). In other embodiments, the control algorithm determines multiple potential pathways for removing candidate debris from the aquatic environment. The controller 102 will navigate the pool cleaner 20 along the pathway having the highest path score. In some embodiments, upon completing the pathway having the highest path score, the algorithm may reevaluate the aquatic environment to determine the next highest path score. The pool cleaner 20 may complete a pathway before beginning another pathway. In some embodiments, the algorithm determines a pathway having a higher path score while the pool cleaner 20 is navigating along a first pathway. The controller 102 may direct the pool cleaner 20 to begin a second pathway before a first pathway.” (Emphasis added). Braidic clearly shows that a robot is moving along a fixed path, as it operates along the path it can determine that there is a higher scoring path, i.e. debris, that it should clean immediately. Braidic’s pathways are fixed in that it operates between fixed control points. Therefore the teachings of Braidic would render this limitation as obvious.
It is noted by the examiner that the applicant claims both a “planned” and a “fixed route.” For purposes of examination the examiner takes a fixed path to be between two or more fixed points. A planned route would be analogous to a pre-planned route, such as corn rows, a spiral path, or some other kind of back and forth movement.
In light of the above the examiner is not convinced by the applicant’s arguments in view of the art as a whole. Therefore the independent claims 1 and 9 would remain rejected under 35 USC 103. The dependent claims are rejected at least due to their dependence on rejected claims as well as any other articulated reasoning. Please see the section below titled, “Claim Rejections – 35 USC 103,” for further detailed mapping and/or explanation.
Claim Objections
Claim 16 is objected to because of the following informalities:
Claim 16 recites, “a fixed route,” in its first limitation, however “a fixed route” has already been claimed by Claim 9, which claim 16 depends on. It should be corrected to, “the fixed route”
Appropriate correction is required.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 1, 3-4, 9, 16, and 19-23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Braidic (US PG Pub 2019/0085579) in view of Attar (US PG Pub 2019/0243379).
Regarding claim 1, Braidic teaches a pool robot control method, comprising:
controlling the pool robot to perform a task in the target water region, ([0047]-[0048] teach the pool cleaning robot performing a task, i.e. patrolling/cleaning, in the target water region, i.e. a pool)
after it is determined that the pool robot completes the task, controlling the pool robot to perform a patrolling operation in the target water region, ([0047]-[0048] and [0054]-[0059] teach the robot patrolling the pool as it moves in a preset path)
in a process in which the pool robot performs the patrolling operation obtaining image information of the target water region captured by the pool robot, ([0042]-[0045] and [0048]-[0049] teach an aquatic robot that obtains images in a target region) wherein the pool robot is capable of operating along a fixed route, ([0047]-[0048] and [0054]-[0059] teach the robot pathing along a preset path between preset points. [0070] teaches that the robot can follow a “singular pathway” i.e. fixed route, along the pool surface to ensure that the pool is cleaned) wherein the image information comprises a frame of image or a plurality of frames of images; ([0048] teaches the robot collecting a series of images at it moves in the environment)
analyzing the image information to determine an analysis result; ([0048]-[0055] teach the system analyzing the image captured by the robot) and
when the pool robot operates along the fixed route, determining a target position of a target object if the analysis result indicates that there is the target object in the target water region, ([0054]-[0055] teaches the robot system tracking the target objects, “debris” in the pool) and controlling the pool robot to move directly to the target position and perform a target operation corresponding to a type of the target object. ([0056]-[0057] teaches the system determining a track to the objects and performing an operation to remove the debris based on the type of debris. [0070] further teaches that as the robot moves along the fixed route, it can determine a new “score” for a higher scoring route, i.e. more debris is in an area. After this determination the pool robot will take a new path to the higher scoring debris directly from its current locale.)
Braidic does not teach wherein the task comprises performing the target operation along an edge of the target water region and performing the target operation in the target water region along a planned route; and the pool robot operates along a random route.
However, Attar teaches “wherein the task comprises performing the target operation along an edge of the target water region and performing the target operation in the target water region along a planned route;” (Figs. 2 and 3B; and [0097]-[0100] and [0115]-[0118] teach the robotic cleaner being tasked with cleaning a pool, i.e. a water region. The system begins by going to the edge of the pool and mapping it, this would perform the target operation along the edge. After the edge is done the robot uses the data gathered to further operate in the pool target, this would be akin to a cleaning path designed as a series of parallel lines, this would be performing the operation in the target region.)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Braidic with Attar; and have a reasonable expectation of success. Both relate to the cleaning operation of pool robots and ensuring that the pool is cleaned effectively. By performing the perimeter/edge cleaning first the robot gains valuable information it can use to determine further cleaning metrics, such as time, duration, etc. This is taught in Attar [0116]. The use of these metrics allows the system to efficiently clean the pool. [0047] of Attar further shows that the edge of the pool/perimeter is useful in determining the direction of travel for the robot. This again allows for efficient mapping of the system.
Regarding claim 3, Braidic teaches the method according to claim 1, wherein the determining a target position of a target object if the analysis result indicates that there is the target object in the target water region, and controlling the pool robot to move to the target position and perform a target operation corresponding to a type of the target object comprises: if the analysis result indicates that there is the target object in the target water region, determining the target position based on the image information; ([0054]-[0055] teaches the robot system tracking the target objects, “debris” in the pool) and
controlling the pool robot to move to the target position and perform the target operation corresponding to the type of the target object. ([0056]-[0057] teaches the system determining a track to the objects and performing an operation to remove the debris based on the type of debris)
Regarding claim 4, Braidic teaches method according to claim 1, wherein the obtaining image information of the target water region captured by the pool robot comprises: obtaining the image information of the target water region captured by the pool robot when the pool robot operates, ([0042]-[0045] and [0048]-[0049] teach the robot operating in a specific control mode and an aquatic robot that obtains images in a target region) between a plurality of preset positions along the fixed route based on a preset time period. ([0047]-[0048] and [0054]-[0059] teach the robot pathing along a preset path between preset points. [0070] teaches that the robot can follow a “singular pathway” i.e. fixed route, along the pool surface to ensure that the pool is cleaned.)
Regarding claim 9, Braidic teaches a pool robot control method, wherein a pool robot is configured to perform a cleaning operation in a target water region, and a camera is disposed on the pool robot, wherein the method comprises: controlling the pool robot to perform a patrolling operation along a fixed route in the target water region, ([0047]-[0048] and [0054]-[0059] teach the robot pathing along a preset path between preset points. [0070] teaches that the robot can follow a “singular pathway” i.e. fixed route, along the pool surface to ensure that the pool is cleaned) enabling the camera to capture an image of the target water region in a process in which the pool robot performs the patrolling operation, ([0042]-[0043] teaches a camera capturing images of the water area where the robot operates) wherein the image is used to determine whether there is a target object in the target water region, wherein the target object needs to be cleaned, ([0048]-[0055] teach the system analyzing the image captured by the robot and determining if there is an object in the target area) wherein the patrolling operation is performed after the pool robot completes a task, ([0047]-[0048] and [0054]-[0059] teach the robot patrolling the pool as it moves in a preset path)
when the pool robot is controller to perform the patrolling operation along the fixed route, controlling, if it is determined that there is the target object, the pool robot to move directly to a target position of the target object and perform the cleaning operation on the target object. ([0056]-[0057] teaches the system determining a track to the objects and performing an operation to remove the debris based on the type of debris. [0070] further teaches that as the robot moves along the fixed route, it can determine a new “score” for a higher scoring route, i.e. more debris is in an area. After this determination the pool robot will take a new path to the higher scoring debris directly from its current locale.)
Braidic does not teach wherein the task comprises performing the target operation along an edge of the target water region and performing the target operation in the target water region along a planned route.
However, Attar teaches “wherein the task comprises performing the target operation along an edge of the target water region and performing the target operation in the target water region along a planned route;” (Figs. 2 and 3B; and [0097]-[0100] and [0115]-[0118] teach the robotic cleaner being tasked with cleaning a pool, water region. The system begins by going to the edge of the pool and mapping it, this would perform the target operation along the edge. After the edge is done the robot uses the data gathered to a further operation along the pool, this would be akin to a cleaning path designed as a series of parallel lines, this would be performing the operation in the target region.)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Braidic with Attar; and have a reasonable expectation of success. Both relate to the cleaning operation of pool robots and ensuring that the pool is cleaned effectively. By performing the perimeter/edge cleaning first the robot gains valuable information it can use to determine further cleaning metrics, such as time, duration, etc. This is taught in Attar [0116]. The use of these metrics allows the system to efficiently clean the pool. [0047] of Attar further shows that the edge of the pool/perimeter is useful in determining the direction of travel for the robot. This again allows for efficient mapping of the system.
Regarding claim 16, Braidic teaches the method according to claim 15, wherein the controlling the pool robot to perform a patrolling operation along a fixed route in the target water region comprises: ([0047]-[0048] teach the robot moving through the environment based on a mode of operation, this includes different kinds of pathing based on the best way to clean the pool): controlling the pool robot to perform the patrolling operation, ([0047]-[0048] and [0054]-[0059] teach the robot operating in a specific control mode) between a plurality of preset positions along the fixed route based on a preset time period. ([0047]-[0048] and [0054]-[0059] teach the robot pathing along a preset path between preset points. [0070] teaches that the robot can follow a “singular pathway” i.e. fixed route, along the pool surface to ensure that the pool is cleaned.)
Regarding claim 19, Braidic teaches the method according to claim 9, comprising: when the pool robot performs the cleaning operation at a water surface or a bottom of the target water region, controlling the pool robot to perform the patrolling operation in the target water region. ([0047] teaches the robot patrolling an aquatic environment. This environment comprises a pool, the robot cleans the entirety of the pool, surface and bottom, and patrols the rest)
Regarding claim 20, Braidic teaches the method according to claim 9, comprising: if it is determined that there is the target object, determining the target position of the target object ([0054]-[0055] teaches the robot system tracking the target objects, “debris” in the pool) and controlling the pool robot to move to the target position of the target object, wherein the image is used to determine the target position of the target object. ([0056]-[0057] teaches the system determining a track to the objects and performing an operation to remove the debris based on the type of debris)
Regarding claim 21, Braidic teaches the method according to claim 1, comprising: when the pool robot performs the cleaning operation at a water surface or a bottom of the target water region, controlling the pool robot to perform the patrolling operation in the target water region. ([0047] teaches the robot patrolling an aquatic environment. This environment comprises a pool, the robot cleans the entirety of the pool, surface and bottom, and patrols the rest)
Regarding claim 22, Braidic teaches the method according to claim 1, wherein the task further comprises performing the target operation along the edge of the target water region again. ([0067] teaches that the robot follows the control algorithm in repeating steps until all debris is cleaned. The system will continuously repeat along paths and edges until every piece of debris is cleaned up.)
Regarding claim 23, Braidic teaches the method according to claim 9, wherein the task further comprises performing the target operation along the edge of the target water region again. ([0067] teaches that the robot follows the control algorithm in repeating steps until all debris is cleaned. The system will continuously repeat along paths and edges until every piece of debris is cleaned up.)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Ding (US PG Pub 2024/0411322) teaches a method and apparatus for cleaning a swimming pool, and an electronic device and a storage medium thereof. The method includes: controlling a swimming pool cleaning robot to move, with respect to a grid map covering the swimming pool, in a work area defined in the swimming pool to establish a cleaning map including a plurality of cleaning blocks; and controlling the swimming pool cleaning robot to traverse each of the cleaning blocks in the cleaning map to clean the swimming pool. According to the present disclosure, the cleaning regions may be accurately constructed in the map according to the work area in the swimming pool, such that the swimming pool cleaning robot cleans the swimming pool in a quick, efficient, and energy-saving fashion.
Duffaut (US PG Pub 2020/0407996) teaches a swimming pool cleaner may include motive elements intentionally driven in an unbalanced manner. This unbalanced driving may allow a cleaner to maintain contact with (“hug”) walls of a pool, allowing the cleaner to, e.g., obtain information allowing mapping of the pool perimeter.
Erlich (US PG Pub 2008/0087299) teaches a method and apparatus for accurately controlling the directional and turning movement of a self-propelled robotic pool cleaner having at least one pair of rotational support members for propelling and cleaning along a surface of a pool or tank include accelerating at least one pair of the rotational support members from a stopped position to a first predetermined rotational rate for a first predetermined time period to propel the pool cleaner in a first direction along the pool surface, continuing the rotation at the first rotational rate for a second predetermined time period; and increasing to a second higher rotational rate, such that the cleaner is propelled at a maximum normalized rate during straight-line movement for cleaning the pool. The duration of straight-line movement is incrementally advanced by a signal that is manually generated by a user switch or a magnet that is brought into proximity of a reed switch mounted inside the cleaner's housing.
Leonessa (US PG Pub 2014/0009748) teaches a pool cleaner control system including a laser range finder with a first laser line generator, a second laser line generator, and a camera. The first laser line generator and the second laser line generator are positioned to emit parallel laser lines and the camera is positioned to capture an image of the laser lines projected on an object. The control system also includes a controller in communication with the laser range finder and configured to control operation of the laser line generators to emit the laser lines and to control the camera to capture the image. The controller is also configured to receive the image from the camera, calculate a pixel distance between the laser lines in the image, and calculate the physical distance between the camera and the object based on the pixel distance.
Schloss (US PG Pub 2018/0135325) teaches a method for remotely operating a robotic pool cleaner may include providing a robotic pool cleaner comprising a housing: a propulsion drive configured to propel the robotic pool cleaner along a surface of a pool; a pump for drawing liquid from the pool into the housing, so as to trap dirt and debris from the surface of the pool into a filter; a controller configured to communicate with a portable communication device, and control the propulsion drive in accordance with commands received from a the portable communication device; using the portable communication device, obtaining one or more characteristics of a surface of the pool; displaying a graphical representation of the pool on a display of the portable communication device; receiving a user input from a user via an input interface of the portable communication device; translating the user input into a command; and transmitting the command to a controller of the robotic pool cleaner, for execution by the robotic pool cleaner.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NICHOLAS STRYKER whose telephone number is (571)272-4659. The examiner can normally be reached Monday-Friday 7:30-5:00.
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, Christian Chace can be reached at (571) 272-4190. 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.
/N.S./Examiner, Art Unit 3665 /CHRISTIAN CHACE/Supervisory Patent Examiner, Art Unit 3665
Prosecution Insights