DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This is a Non-Final Action on the Merits. Claims 1-24 are currently pending and are addressed below.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 March 5th, 2026 has been entered.
Response to Amendments
The amendment filed on March 5th, 2026 has been considered and entered. Accordingly, claims 1, 11-13, 19, and 22 has been amended. Claims 23-24 have been newly added.
Response to Arguments
The Applicant states (Amend. 7) that the claims 1-24 are directed to statutory subject matter and that the independent claims provide a specific solution to a technological problem and are not an abstract idea. The examiner respectfully disagrees. Amended claim 1 at most discusses an abstract idea to determine a traveling boundary . Even if, for the sake of the argument, the determination is a new idea, “a claim for a new abstract idea is still an abstract idea.” Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151 (Fed. Cir. 2016) (emphasis omitted); see also Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016) (“A narrow claim directed to an abstract idea, however, is not necessarily patent-eligible.”). Furthermore, when a claim directed to an abstract idea contains no restriction on how an asserted improvement is accomplished and the asserted improvement is not described in the claim, then the claim does not become patent eligible. See Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1316 (Fed. Cir. 2016). Furthermore, the applicants assert arguments for a more general improvement to an existing technological process. However, the applicant’s arguments are not persuasive because applicant’s claim 1 fails to recite (1) any limitations detailing “low demand services”, how to efficiently “uninstall and then reinstall a service” or how management of services are allowed to be more efficient, and (2) any limitations detailing how “allowing the service requester to receive a desired quality of service” or how “not experiencing a delay or difference in quality of service even if the requested service had its processing priority lowered and needed to be reconfigured” is achieved. When a claim directed to an abstract idea contains no restriction on how an asserted improvement is accomplished and the asserted improvement is not described in the claim, then the claim does not become patent eligible. See Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1316 (Fed. Cir. 2016); see also MPEP 2106.04(d)(1) (“Second, if the specification sets forth an improvement in technology, the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement. That is, the claim includes the components or steps of the invention that provide the improvement described in the specification”).
The Applicant’s arguments with respect to claims 1-24 have been considered but are moot in view of the newly formulated grounds of rejection necessitated by the applicant’s amendments.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-24 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without significantly more.
In sum, claims 1-24 are rejected under 35 U.S.C. §101 because the claimed invention is directed to a judicial exception to patentability (i.e., a law of nature, a natural phenomenon, or an abstract idea) and do not include an inventive concept that is something “significantly more” than the judicial exception under the January 2019 patentable subject matter eligibility guidance (2019 PEG) analysis which follows.
Under the 2019 PEG step 1 analysis, it must first be determined whether the claims are directed to one of the four statutory categories of invention (i.e., process, machine, manufacture, or composition of matter). Applying step 1 of the analysis for patentable subject matter to the claims, it is determined that the claims are directed to the statutory category of a process. Therefore, we proceed to step 2A, Prong 1.
Revised Guidance Step 2A – Prong 1
Under the 2019 PEG step 2A, Prong 1 analysis, it must be determined whether the claims recite an abstract idea that falls within one or more designated categories of patent ineligible subject matter (i.e., organizing human activity, mathematical concepts, and mental processes) that amount to a judicial exception to patentability.
Here, with respect to independent claims 1, 12, and 19, the claims recite the abstract idea of modify a boundary for a cleaning robot, and mentally determine “generate a boundary of traversable space by the mobile cleaning robot within the environment using the sensor data, the boundary of traversable space at least partially defining non-traversable space of the environment, and the non-traversable space including a region beyond the boundary of traversable space but within the environment; and generate a modified boundary of the environment using the non-traversable space and the sensor data”, where these claims fall within one or more of the three enumerated 2019 PEG categories of patent ineligible subject matter, specifically, a mental process, that can be performed in the human mind since each of the above steps could alternatively be performed in the human mind or with the aid of pen and paper. This conclusion follows from CyberSource Corp. v. Retail Decisions, Inc., where our reviewing court held that section 101 did not embrace a process defined simply as using a computer to perform a series of mental steps that people, aware of each step, can and regularly do perform in their heads. 654 F.3d 1366, 1373 (Fed. Cir. 2011); see also In re Grams, 888 F.2d 835, 840–41 (Fed. Cir. 1989); In re Meyer, 688 F.2d 789, 794–95 (CCPA 1982); Elec. Power Group, LLC v. Alstom S.A., 830 F. 3d 1350, 1354–1354 (Fed. Cir. 2016) (“we have treated analyzing information by steps people go through in their minds, or by mathematical algorithms, without more, as essentially mental processes within the abstract-idea category”).
Additionally, mental processes remain unpatentable even when automated to reduce the burden on the user of what once could have been done with pen and paper. See CyberSource, 654 F.3d at 1375 (“That purely mental processes can be unpatentable, even when performed by a computer, was precisely the holding of the Supreme Court in Gottschalk v. Benson.”). These limitations, as drafted, are a simple process that under their broadest reasonable interpretation, covers the performance of the limitations of the mind. For example, the claim limitation encompasses mentally generating a boundary of an environment based off of the information provided by the robot’s sensors while traveling, or alternatively, mentally generating a boundary of an environment based on observations by a human.
For example, a human could mentally and with the aid of pen and paper generating a boundary of an environment.
Revised Guidance Step 2A – Prong 2
Under the 2019 PEG step 2A, Prong 2 analysis, the identified abstract idea to which the claim is directed does not include limitations that integrate the abstract idea into a practical application, since the additional elements of a robot’s sensors and memory are merely generic components used as a tool (“apply it”) to implement the abstract idea. (See, e.g., MPEP §2106.05(f)). See Alice, 573 U.S. at 223 (“[T]he mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention.”)
In addition, the limitation “receive sensor data from a mobile cleaning robot based on interactions between the mobile cleaning robot and an environment” constitutes insignificant presolution activity that merely gathers data and, therefore, do not integrate the exception into a practical application. See In re Bilski, 545 F.3d 943, 963 (Fed. Cir. 2008) (en banc), aff' d on other grounds, 561 U.S. 593 (2010) (characterizing data gathering steps as insignificant extra-solution activity); see also CyberSource, 654 F.3d at 1371–72 (noting that even if some physical steps are required to obtain information from a database (e.g., entering a query via a keyboard, clicking a mouse), such data-gathering steps cannot alone confer patentability); OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering). Accord Guidance, 84 Fed. Reg. at 55 (citing MPEP § 2106.05(g)).
In addition, merely “[u]sing a computer to accelerate an ineligible mental process does not make that process patent-eligible.” Bancorp Servs., L.L.C. v. Sun Life Assur. Co. of Canada (U.S.), 687 F.3d 1266, 1279 (Fed. Cir. 2012); see also CLS Bank Int’l v. Alice Corp. Pty. Ltd., 717 F.3d 1269, 1286 (Fed. Cir. 2013) (en banc) (“simply appending generic computer functionality to lend speed or efficiency to the performance of an otherwise abstract concept does not meaningfully limit claim scope for purposes of patent eligibility.”), aff’d, 573 U.S. 208 (2014). Accordingly, the additional element of a processor does not transform the abstract idea into a practical application of the abstract idea.
Revised Guidance Step 2B
Under the 2019 PEG step 2B analysis, the additional elements are evaluated to determine whether they amount to something “significantly more” than the recited abstract idea. (i.e., an innovative concept). Here, the additional elements, such as: a sensor and a memory does not amount to an innovative concept since, as stated above in the step 2A, Prong 2 analysis, the claims are simply using the additional elements as a tool to carry out the abstract idea (i.e., “apply it”) on a computer or computing device and/or via software programming. (See, e.g., MPEP §2106.05(f)). The additional elements are specified at a high level of generality to simply implement the abstract idea and are not themselves being technologically improved. (See, e.g., MPEP §2106.05 I.A.). See Alice, 573 U.S. at 223 (“[T]he mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention.”). Thus, these elements, taken individually or together, do not amount to “significantly more” than the abstract ideas themselves.
The additional elements of the dependent claims 2-11, 13-18, and 20-24 merely refine and further limit the abstract idea of the independent claims and do not add any feature that is an “inventive concept” which cures the deficiencies of their respective parent claim under the 2019 PEG analysis. None of the dependent claims considered individually, including their respective limitations, include an “inventive concept” of some additional element or combination of elements sufficient to ensure that the claims in practice amount to something “significantly more” than patent-ineligible subject matter to which the claims are directed.
The elements of the instant claimed invention, when taken in combination do not offer substantially more than the sum of the functions of the elements when each is taken alone. The claims as a whole, do not amount to significantly more than the abstract idea itself because the claims do not effect an improvement to another technology or technical field; the claims do not amount to an improvement to the functioning of an electronic device itself which implements the abstract idea (e.g., the general purpose computer and/or the computer system which implements the process are not made more efficient or technologically improved); the claims do not perform a transformation or reduction of a particular article to a different state or thing (i.e., the claims do not use the abstract idea in the claimed process to bring about a physical change. See, e.g., Diamond v. Diehr, 450 U.S. 175 (1981), where a physical change, and thus patentability, was imparted by the claimed process; contrast, Parker v. Flook, 437 U.S. 584 (1978), where a physical change, and thus patentability, was not imparted by the claimed process); and the claims do not move beyond a general link of the use of the abstract idea to a particular technological environment (e.g., “of generating a map of an environment using a mobile cleaning robot. . . sensors” claim 12).
Accordingly, claims 1-24 are rejected under 35 USC 101 as being drawn to an abstract idea without significantly more, and thus are ineligible.
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 (i.e., changing from AIA to pre-AIA ) 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.
Claims 1-5, 12, 14-16, 19-21, and 23-24 are rejected under 35 U.S.C. 103 as being unpatentable over Kleiner (US 20180074508 A1) (“Kleiner”) in view of Herlant (US 20220206507 A1) (“Herlant”).
With respect to claim 1, Kleiner teaches at least one non-transitory machine-readable medium, including instructions, which when executed, cause processing circuitry to perform operations to:
receive sensor data from a mobile cleaning robot based on interactions between the mobile cleaning robot and an environment (See at least Kleiner Paragraph 7 “In some embodiments, the computing device may be a component of the mobile robot, and the occupancy data may be detected by at least one sensor of the mobile robot. The operations may further include operating a drive of the mobile robot to sequentially navigate the non-clutter and clutter areas of the at least one of the respective regions of the surface in the sequence indicated by the coverage pattern.”);
generate a boundary of traversable space by the mobile cleaning robot within the environment using the sensor data (See at least Kleiner Paragraph 5 “Some embodiments of the present invention include a method of operating a mobile robot. The method includes executing, by at least one processor, computer readable instructions stored in a non-transitory computer readable storage medium to perform operations including generating a segmentation map defining respective regions of a surface based on occupancy data that is collected by the mobile robot responsive to navigation of the surface, classifying or otherwise identifying sub-regions of at least one of the respective regions as non-clutter and clutter areas, and computing a coverage pattern based on identification of the sub-regions. The coverage pattern indicates a sequence for navigation of the non-clutter and clutter areas, and is provided to the mobile robot. Responsive to the coverage pattern, the mobile robot sequentially navigates the non-clutter and clutter areas of the at least one of the respective regions of the surface in the sequence indicated by the coverage pattern.” | Paragraphs 222-223); and
generate a modified boundary of the environment using the sensor data (See at least Kleiner Paragraphs 20-30 “In some embodiments, the segmentation map may include simplified boundaries relative to actual boundaries indicated by the occupancy data collected by the mobile robot responsive to navigation of the surface. In some embodiments, the operations may further include modifying the segmentation map having the simplified boundaries to indicate the clutter areas responsive to identification thereof prior to providing the segmentation map to a user device. In some embodiments, identifying the sub-regions as non-clutter and clutter areas may further include accessing a data store comprising a plurality of patterns and identifications thereof, and classifying pixel regions within the sub-regions based on similarities to the plurality of patterns stored in the data store. … Some embodiments provide that the modified segmentation map identifies a subset of the plurality of regions to be cleaned, the subset including a portion of one of the plurality of regions, and the modified segmentation map identifies an order in which the plurality of regions are to be cleaned …” | Paragraphs 222-223).
Kleiner, however, fails to explicitly disclose that the boundary of traversable space at least partially defining non- traversable space of the environment, the non-traversable space including a region beyond the boundary of traversable space but within the environment; and generate a modified boundary of the environment using the non-traversable space and the sensor data.
Herlant teaches that the boundary of traversable space at least partially defining non- traversable space of the environment, the non-traversable space including a region beyond the boundary of traversable space but within the environment; and generate a modified boundary of the environment using the non-traversable space and the sensor data (See at least Herlant Paragraph 77 “As the controller circuit 109 directs the mobile robot 100 about the floor surface 10 during the mission, the controller circuit 109 uses SLAM techniques to determine a location of the mobile robot 100 within the map by detecting features represented in collected sensor data and comparing the features to previously stored features. The map formed from the sensor data can indicate locations of traversable and nontraversable space within the environment. For example, locations of obstacles are indicated on the map as nontraversable space, and locations of open floor space are indicated on the map as traversable space”).
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 of Kleiner to include that the boundary of traversable space at least partially defining non- traversable space of the environment, the non-traversable space including a region beyond the boundary of traversable space but within the environment; and generate a modified boundary of the environment using the non-traversable space and the sensor data, as taught by Herlant as disclosed above, in order to ensure accurate traversal of the mobile cleaning robot (Herlant Paragraph 1 “This document relates generally to mobile robots and, more particularly, to systems, devices, and methods for validating a dock location for docking a mobile robot”).
With respect to claim 2, and similarly claim 20, Kleiner in view of Herlant teaches to generate a map of the environment based on the modified boundary (See at least Kleiner FIG. 5 and Paragraph 136 “FIG. 5 is a block diagram illustrating a method for operating a mobile floor cleaning robot according to some embodiments of the present invention. The method includes generating a segmentation map of a surface of an enclosed space or other operating environment using the mobile floor cleaning robot 100 to identify multiple regions of the surface (block 504). In some embodiments, an enclosed space may include an occupancy, whether occupied or not, including, for example, a residential building, a commercial building, a storage building, a manufacturing building and/or a portion thereof.”).
With respect to claim 3, and similarly claims 14 and 21, Kleiner in view of Herlant teaches to segment the map into rooms defined by room boundaries based at least in part on the modified boundary (See at least Kleiner Paragraph 11 “In some embodiments, the respective regions defined by the segmentation map may correspond to respective rooms. The coverage pattern may further indicate an order of navigation of the respective rooms, and the mobile robot may sequentially navigate the non-clutter and clutter areas of one of the respective rooms in the sequence indicated by the coverage pattern before navigation of a next one of the respective rooms in the order indicated by the coverage pattern.”).
With respect to claim 4, and similarly claim 15, Kleiner in view of Herlant teaches that the map is segmented into rooms based at least in part on the non-traversable space (See at least Kleiner Paragraph 184-186 “FIGS. 8A through 8C are graphical representations that may be displayed via a user interface of a communication device illustrating a raw data map, a cleaned map and a segmentation map in an automated map cleaning and segmentation operation according to some embodiments of the present invention. Some embodiments provide that a robot explores a surface of an enclosed space during a first pass. An occupancy grid is generated that includes raw data that is generated during the first pass. The occupancy grid is presented to a user on a user device as a raw data map 802 as illustrated in FIG. 8A. The raw data map 802 may include multiple pixels that may be shaded white for traversable space and black for obstacles, including occupancy walls … FIG. 8C illustrates a segmentation map 822 that may be displayed to the user on the user device. Similar to the cleaned map 812, the segmentation map 822 illustrates the enclosed space with the boundary data 826. Additionally, the traversable space is segmented into regions 824 that may correspond to different rooms in the enclosed space according to some embodiments. Based on the segmentation map 822, the robot may perform room-by-room cleaning in which the cleaning operation in a given region 824 is completed before the robot begins to perform a cleaning operation in another region 824.”).
With respect to claim 5, and similarly claim 16, Kleiner in view of Herlant teaches to characterize1 portions of the non-traversable space using the sensor data (See at least Kleiner Paragraph 184-186 “FIGS. 8A through 8C are graphical representations that may be displayed via a user interface of a communication device illustrating a raw data map, a cleaned map and a segmentation map in an automated map cleaning and segmentation operation according to some embodiments of the present invention. Some embodiments provide that a robot explores a surface of an enclosed space during a first pass. An occupancy grid is generated that includes raw data that is generated during the first pass. The occupancy grid is presented to a user on a user device as a raw data map 802 as illustrated in FIG. 8A. The raw data map 802 may include multiple pixels that may be shaded white for traversable space and black for obstacles, including occupancy walls … FIG. 8C illustrates a segmentation map 822 that may be displayed to the user on the user device. Similar to the cleaned map 812, the segmentation map 822 illustrates the enclosed space with the boundary data 826. Additionally, the traversable space is segmented into regions 824 that may correspond to different rooms in the enclosed space according to some embodiments. Based on the segmentation map 822, the robot may perform room-by-room cleaning in which the cleaning operation in a given region 824 is completed before the robot begins to perform a cleaning operation in another region 824.”).
With respect to claim 12, Kleiner teaches a method of generating a map of an environment using a mobile cleaning robot, the method comprising:
receive sensor data from a mobile cleaning robot based on interactions between the mobile cleaning robot and an environment (See at least Kleiner Paragraph 7 “In some embodiments, the computing device may be a component of the mobile robot, and the occupancy data may be detected by at least one sensor of the mobile robot. The operations may further include operating a drive of the mobile robot to sequentially navigate the non-clutter and clutter areas of the at least one of the respective regions of the surface in the sequence indicated by the coverage pattern.”);
generate a boundary of traversable space by the mobile cleaning robot within the environment using the sensor data (See at least Kleiner Paragraph 5 “Some embodiments of the present invention include a method of operating a mobile robot. The method includes executing, by at least one processor, computer readable instructions stored in a non-transitory computer readable storage medium to perform operations including generating a segmentation map defining respective regions of a surface based on occupancy data that is collected by the mobile robot responsive to navigation of the surface, classifying or otherwise identifying sub-regions of at least one of the respective regions as non-clutter and clutter areas, and computing a coverage pattern based on identification of the sub-regions. The coverage pattern indicates a sequence for navigation of the non-clutter and clutter areas, and is provided to the mobile robot. Responsive to the coverage pattern, the mobile robot sequentially navigates the non-clutter and clutter areas of the at least one of the respective regions of the surface in the sequence indicated by the coverage pattern.” | Paragraphs 222-223); and
generate a modified boundary of the environment using the sensor data (See at least Kleiner Paragraphs 20-30 “In some embodiments, the segmentation map may include simplified boundaries relative to actual boundaries indicated by the occupancy data collected by the mobile robot responsive to navigation of the surface. In some embodiments, the operations may further include modifying the segmentation map having the simplified boundaries to indicate the clutter areas responsive to identification thereof prior to providing the segmentation map to a user device. In some embodiments, identifying the sub-regions as non-clutter and clutter areas may further include accessing a data store comprising a plurality of patterns and identifications thereof, and classifying pixel regions within the sub-regions based on similarities to the plurality of patterns stored in the data store. … Some embodiments provide that the modified segmentation map identifies a subset of the plurality of regions to be cleaned, the subset including a portion of one of the plurality of regions, and the modified segmentation map identifies an order in which the plurality of regions are to be cleaned …” | Paragraphs 222-223).
Kleiner, however, fails to explicitly disclose that the boundary of traversable space at least partially defining non- traversable space of the environment, the non-traversable space including a region beyond the boundary of traversable space but within the environment; generate a modified boundary of the environment using the non-traversable space and the sensor data; generate a map of the environment based on the modified boundary.
Herlant teaches that the boundary of traversable space at least partially defining non- traversable space of the environment, the non-traversable space including a region beyond the boundary of traversable space but within the environment; generate a modified boundary of the environment using the non-traversable space and the sensor data; generate a map of the environment based on the modified boundary (See at least Herlant Paragraph 77 “As the controller circuit 109 directs the mobile robot 100 about the floor surface 10 during the mission, the controller circuit 109 uses SLAM techniques to determine a location of the mobile robot 100 within the map by detecting features represented in collected sensor data and comparing the features to previously stored features. The map formed from the sensor data can indicate locations of traversable and nontraversable space within the environment. For example, locations of obstacles are indicated on the map as nontraversable space, and locations of open floor space are indicated on the map as traversable space”).
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 of Kleiner to include that the boundary of traversable space at least partially defining non- traversable space of the environment, the non-traversable space including a region beyond the boundary of traversable space but within the environment; generate a modified boundary of the environment using the non-traversable space and the sensor data; generate a map of the environment based on the modified boundary, as taught by Herlant as disclosed above, in order to ensure accurate traversal of the mobile cleaning robot (Herlant Paragraph 1 “This document relates generally to mobile robots and, more particularly, to systems, devices, and methods for validating a dock location for docking a mobile robot”).
With respect to claim 19, Kleiner teaches at least one non-transitory machine-readable medium, including instructions, which when executed, cause processing circuitry to perform operations to:
receive sensor data from a mobile cleaning robot based on interactions between the mobile cleaning robot and an environment (See at least Kleiner Paragraph 7 “In some embodiments, the computing device may be a component of the mobile robot, and the occupancy data may be detected by at least one sensor of the mobile robot. The operations may further include operating a drive of the mobile robot to sequentially navigate the non-clutter and clutter areas of the at least one of the respective regions of the surface in the sequence indicated by the coverage pattern.”);
generate a boundary of traversable space by the mobile cleaning robot within the environment using the sensor data (See at least Kleiner Paragraph 5 “Some embodiments of the present invention include a method of operating a mobile robot. The method includes executing, by at least one processor, computer readable instructions stored in a non-transitory computer readable storage medium to perform operations including generating a segmentation map defining respective regions of a surface based on occupancy data that is collected by the mobile robot responsive to navigation of the surface, classifying or otherwise identifying sub-regions of at least one of the respective regions as non-clutter and clutter areas, and computing a coverage pattern based on identification of the sub-regions. The coverage pattern indicates a sequence for navigation of the non-clutter and clutter areas, and is provided to the mobile robot. Responsive to the coverage pattern, the mobile robot sequentially navigates the non-clutter and clutter areas of the at least one of the respective regions of the surface in the sequence indicated by the coverage pattern.” | Paragraphs 222-223); and
generate a modified boundary of the environment using the sensor data (See at least Kleiner Paragraphs 20-30 “In some embodiments, the segmentation map may include simplified boundaries relative to actual boundaries indicated by the occupancy data collected by the mobile robot responsive to navigation of the surface. In some embodiments, the operations may further include modifying the segmentation map having the simplified boundaries to indicate the clutter areas responsive to identification thereof prior to providing the segmentation map to a user device. In some embodiments, identifying the sub-regions as non-clutter and clutter areas may further include accessing a data store comprising a plurality of patterns and identifications thereof, and classifying pixel regions within the sub-regions based on similarities to the plurality of patterns stored in the data store. … Some embodiments provide that the modified segmentation map identifies a subset of the plurality of regions to be cleaned, the subset including a portion of one of the plurality of regions, and the modified segmentation map identifies an order in which the plurality of regions are to be cleaned …” | Paragraphs 222-223).
Kleiner, however, fails to explicitly disclose that the boundary of traversable space at least partially defining non- traversable space of the environment, the non-traversable space including a region beyond the boundary of traversable space but within the environment; and generate a modified boundary of the environment using the non-traversable space and the sensor data.
Herlant teaches that the boundary of traversable space at least partially defining non- traversable space of the environment, the non-traversable space including a region beyond the boundary of traversable space but within the environment; and generate a modified boundary of the environment using the non-traversable space and the sensor data (See at least Herlant Paragraph 77 “As the controller circuit 109 directs the mobile robot 100 about the floor surface 10 during the mission, the controller circuit 109 uses SLAM techniques to determine a location of the mobile robot 100 within the map by detecting features represented in collected sensor data and comparing the features to previously stored features. The map formed from the sensor data can indicate locations of traversable and nontraversable space within the environment. For example, locations of obstacles are indicated on the map as nontraversable space, and locations of open floor space are indicated on the map as traversable space”).
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 of Kleiner to include that the boundary of traversable space at least partially defining non- traversable space of the environment, the non-traversable space including a region beyond the boundary of traversable space but within the environment; and generate a modified boundary of the environment using the non-traversable space and the sensor data, as taught by Herlant as disclosed above, in order to ensure accurate traversal of the mobile cleaning robot (Herlant Paragraph 1 “This document relates generally to mobile robots and, more particularly, to systems, devices, and methods for validating a dock location for docking a mobile robot”).
With respect to claim 23, Kleiner in view of Herlant teach to replace a portion of the boundary of traversable space abutting an inner perimeter of a non- traversable space with an outer perimeter of the non-traversable space (See at least Kleiner Paragraph 223 “Accordingly, a coverage pattern may be determined and provided to the robot 100 such that the robot 100 first cleans the elongated corridor 2904 by efficient ranking without entering the shoe-cluttered area 2906. After executing the cleaning of the elongated corridor 2904, the robot 100 will sequentially clean the clutter area 2906 (to the left of the corridor) by edge cleaning, according to the coverage pattern. However, if people subsequently begin placing shoes near the right wall of the elongated corridor 2904 (and no longer in the area 2906 to the left), the area classifications and coverage pattern may be modified responsive to detection of this change after subsequent navigations, and the robot 100 may observably alter its cleaning behavior after a few cleaning runs. More particularly, the coverage pattern may be modified such that, in response to the coverage pattern, the robot 100 may first clean the now-open area (formerly classified as clutter area 2906) on the left side of the elongated corridor 2904, and then execute edge cleaning on the shoe-cluttered area along the right wall of the elongated corridor 2904. More generally, there may be multiple indications of clutter detection during navigation of the robot 100. These may include, but are not limited to, display and marking of the clutter areas 2906 and open areas 2904 via the user interface of a user device 202, different behavior of the robot 100 in navigating the open areas 2904 and clutter areas 2906, and repeated execution of the different behaviors in the same order or sequence (as well as changes to the repeated execution responsive to changes in the environment).”).
With respect to claim 24, Kleiner in view of Herlant teach that the non-traversable space includes space between an obstacle that physically prevents the mobile cleaning robot from traversing beyond the obstacle and a wall defining an edge of the environment (See at least Kleiner Paragraph 146 “For example, a robot attempting to wall follow along an edge of an obstacle or collection of obstacles constituting clutter may detect and avoid the clutter by turning left and/or right at least three times in a distance of less than 5 feet. For example, a robot attempting to wall follow along an edge of an obstacle or collection of obstacles constituting clutter may detect and avoid the clutter by turning left and/or right at least three times in a distance spanning the length of the clutter over a length of 10 feet or less. For example, a robot encountering an obstacle or collection of obstacles constituting clutter may detect and avoid the clutter by turning from a forward heading at least three times in a two foot distance. For example, a robot encountering an obstacle or collection of obstacles constituting clutter may detect and avoid the clutter by turning left and/or right at least three times in a distance of less than 10 feet along one primary direction and at least 10 feet along a direction orthogonal to the primary direction so as to identify an outer boundary of the clutter region.”).
Claims 6-8, 11, 13, 17, and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Kleiner (US 20180074508 A1) (“Kleiner”) in view of Herlant (US 20220206507 A1) (“Herlant”) in view of Williams (US 20200238520 A1) (“Williams”).
With respect to claim 6, and similarly claim 17, Kleiner in view of Herlant fails to explicitly disclose to modify the room boundaries based at least in part on the characterized portions of the non-traversable space.
Williams teaches to modify the room boundaries based at least in part on the characterized portions of the non-traversable space (See at least Williams FIG. 7C and Paragraphs 105-107 “At operation 680, the robot detects the markers in the environment. The controller can use a camera, ultrasonic sensor, or some other sensor on the robot to detect the markers. In some cases, as described herein, the camera may detect a color, image, or other distinctive feature of the markers. The controller can receive image data from the camera corresponding to the detection of the markers. At operation 682, the controller determines whether the detected markers are virtual barrier markers. The controller may also post-process the image data of the detected markers and make a determination of whether the image data correspond to reference images that the controller may expect from detecting the markers. The controller may compare the image data to reference images in a library stored on a memory storage element operable with the controller. The controller can determine whether the detected markers indicate a virtual barrier, a location, or other information about the environment. If the controller determines that the detected markers are virtual barrier markers, at operation 684, the controller generates a virtual barrier in an occupancy grid that, for example, corresponds to the location of the detected markers. The virtual barrier, as described herein, can correspond to a set of non-traversable cells to be marked on the occupancy grid. In some cases, the length or width of the non-traversable barrier may depend on distinctive features detected on the markers. If the controller determines that the detected marker is not a virtual barrier marker, at operation 686, the controller stores data related to the detected marker in the occupancy grid. The data may be, for example, a name of the room, a name of the location of the detected markers. In some implementations, the controller may determine that the controller has misidentified the detected markers and that the detected markers do not indicate information about the environment. In some examples, the controller may determine that the detected markers indicate both a virtual barrier and data related to the name of the room or the location of the detected markers”).
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 of Kleiner in view of Herlant to modify the room boundaries based at least in part on the characterized portions of the non-traversable space, as taught by Williams as disclosed above, in order to ensure accurate boundaries of various areas that the cleaning robot will traverse (Williams Paragraph 15 “The robot can be restricted to areas where the robot can move freely while reducing the risk of damage to objects in the area”).
With respect to claim 7, Kleiner in view of Herlant in view of Williams teach that the portions are characterized using images captured by an image capture device of the cleaning of the mobile cleaning robot (See at least Kleiner Paragraph 118 “The environmental sensors 270A-270H may include a camera 270B mounted on a top surface of the mobile robot 100, as shown in the top perspective view of FIG. 2A. The camera 270B can be used to navigate the robot 100 and acquire images for other operational use. In some embodiments, the camera 270B is a visual simultaneous location and mapping (VSLAM) camera and is used to detect features and landmarks in the operating environment and build an occupancy map based thereon.”).
With respect to claim 8, Kleiner in view of Herlant in view of Williams teach that the images are captured using a VSLAM process (See at least Kleiner Paragraph 137 “In some embodiments, the segmentation map is generated from an occupancy grid that is generated by the mobile floor cleaning robot during one or more exploration and/or cleaning missions, more generally referred to herein as navigation. For example, the occupancy grid may be generated by exploring the surface of the enclosed space with the mobile floor cleaning robot by generating one or more visual maps for localization of the mobile floor cleaning robot within the enclosed space. In some embodiments, the visual maps may be generated by detecting features using multiple images that may be captured by one or more cameras in the mobile floor cleaning robot. For example, visual features (VSLAM) generated from the video images may be used in order build the “visual map” used to localize the robot. For each feature, a feature description may be determined and the feature may be classified by performing a feature lookup in a feature database. The occupancy grid may be integrated with the visual map, and may further include information generated from bumper hits or collisions (“bumping” events) and/or IR/PixArt data (i.e., time of flight and/or ranging sensor data for obstacle detection).”).
With respect to claim 11, and similarly claims 13 and 22, Kleiner in view of Herlant fails to explicitly disclose that the non-traversable space includes space beyond the boundary of traversable space that has been observed by the mobile cleaning robot and has not been traversed by the mobile cleaning robot.
Williams teaches that the non-traversable space includes space beyond the boundary of traversable space that has been observed by the mobile cleaning robot and has not been traversed by the mobile cleaning robot. (See at least Williams Paragraph 74 “In some cases, the virtual barrier 516 passes through the back side 202A of the robot 200. In other cases, the virtual barrier 516 intersects the robot body, e.g., the virtual barrier passes through the lights 242 a and 242 b enabling the user to align the lights with the location of the virtual barrier. The lights 242 a and 242 b therefore may serve as visual indicators of the location of the virtual barrier 516. The virtual barrier 516 can prevent the robot 200 from passing from the first room 504 through a doorway 517 into the room 506 of the environment 502. In some implementations, the robot can be placed in the doorway 517 so that the controller generates the virtual barrier 516 that prevents the robot 200 from passing through the doorway 517.”).
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 of Kleiner in view of Herlant so that the non-traversable space includes space beyond the boundary of traversable space that has been observed by the mobile cleaning robot and has not been traversed by the mobile cleaning robot, as taught by Williams as disclosed above, in order to ensure accurate boundaries of various areas that the cleaning robot will traverse (Williams Paragraph 15 “The robot can be restricted to areas where the robot can move freely while reducing the risk of damage to objects in the area”).
Claims 9-10 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Kleiner (US 20180074508 A1) (“Kleiner”) in view of Herlant (US 20220206507 A1) (“Herlant”) in view of Williams (US 20200238520 A1) (“Williams”) further in view of Afrouzi (US 20200409376 A1) (“Afrouzi”).
With respect to claim 9, and similarly claim 18, Kleiner in view of Herlant in view of Williams fails to explicitly disclose to determine a height of the characterized portions using the sensor data; and generate a three dimensional representation for each of the characterized portions using the map and the height of the characterized portions.
Afrouzi teaches determine a height of the characterized portions using the sensor data (See at least Afrouzi Paragraph 187 “In some embodiments, the map may be a state space with possible values for x, y, z. In some embodiments, a value of x and y may be a point on a Cartesian plane on which the robot drives and the value of z may be a height of obstacles or depth of cliffs. In some embodiments, the map may include additional dimensions (e.g., debris accumulation, floor type, obstacles, cliffs, stalls, etc.)”); and
generate a three dimensional representation for each of the characterized portions using the map and the height of the characterized portions (See at least Afrouzi Paragraph 345 “FIG. 123A illustrates a flowchart depicting the combination of SLAM and AR. A SLAM enabled device 6500 (e.g., robot 6501, smart phone 6502, smart glasses, 6503, smart watch 6504, and virtual reality goggles 6505, etc.) generates information 6506, such as an environmental map, 3D outline of the environment, and other environmental data (e.g., temperature, debris accumulation, floor type, edges, previous collisions, etc.), and places them as overlaid layers of a video feed of the same environment in real time 6502 …”).
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 of Kleiner in view of Herlant in view of Williams to include to determine a height of the characterized portions using the sensor data; and generate a three dimensional representation for each of the characterized portions using the map and the height of the characterized portions, as taught by Afrouzi as disclosed above, in order to ensure an accurate map for the cleaning robot to traverse (Afrouzi Abstract “Provided is a method for operating a robot, including capturing images of a workspace, comparing at least one object from the captured images to objects in an object dictionary, identifying a class to which the at least one object belongs using an object classification unit, instructing the robot to execute at least one action based on the object class identified, capturing movement data of the robot, and generating a planar representation of the workspace based on the captured images and the movement data, ”).
With respect to claim 10, Kleiner in view of Herlant in view of Williams in view of Afrouzi teach to generate a three dimensional map based on the map and based on the three dimensional representations of the characterized portions (See at least Afrouzi Paragraph 345 “FIG. 123A illustrates a flowchart depicting the combination of SLAM and AR. A SLAM enabled device 6500 (e.g., robot 6501, smart phone 6502, smart glasses, 6503, smart watch 6504, and virtual reality goggles 6505, etc.) generates information 6506, such as an environmental map, 3D outline of the environment, and other environmental data (e.g., temperature, debris accumulation, floor type, edges, previous collisions, etc.), and places them as overlaid layers of a video feed of the same environment in real time 6502 … FIG. 123E illustrates an example of a video of a camera feed with several layers of overlaid information, such as dimensions 6508, a three dimensional map of perimeters 6509, dynamic obstacle 6510, and information 6511. Because of SLAM, hidden elements, such as dynamic obstacle 6510 positioned behind a wall, may be shown. FIG. 123F illustrates the different layers 6512 that are overlaid on the video illustrated in FIG. 123E. FIG. 123G illustrates an example of an overlay of a map of an environment 6513 on a video of a camera feed observing the same environment.”).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to IBRAHIM ABDOALATIF ALSOMAIRY whose telephone number is (571)272-5653. The examiner can normally be reached M-F 7:30-5:30.
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/IBRAHIM ABDOALATIF ALSOMAIRY/Examiner, Art Unit 3667
/FARIS S ALMATRAHI/Supervisory Patent Examiner, Art Unit 3667
1 There is no limiting definition as to what constitutes to characterize, but the published specification states in paragraph 77 “For example, based on the sensor data and the map, spaces or objects can be characterized as walls or other immobile objects”
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