DETAILED ACTION
Claims 1-8, 10-19 and 21 are pending in this application. Claims 1-8, 10-19 and 21 have been examined with the priority date of 10/07/2022 in accordance with the applicant’s claim for foreign priority. Claims 1, 3, 10-11, 13 and 21 are amended and claims 9 and 20 are canceled.
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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 08/03/2023, 01/09/2024, and 12/27/2024 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 04/29/2026 has been entered.
Response to Arguments
Claim interpretation under 35 U.S.C. 112(f)
Applicants’ arguments (see Remarks filed 04/29/2026) have been fully considered by the examiner and are persuasive in view of the amendments to the claims. Accordingly, the claim interpretations under 35 U.S.C. 112(f) have been withdrawn.
Claim rejections under 35 U.S.C. 103
Applicant’s arguments (see Remarks filed 04/29/2026) with respect to rejection under 35 U.S.C. 103 have been fully considered by the examiner and are persuasive. In view of the amendments to the scope of claims 1, 10 and 11, a new grounds of rejection is made over Sinyavskiy in view of Jakhotia as fully discussed below.
Objections
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed. The examiner respectfully suggests the following title; “METHOD OF CONTROLLING ELECTRONIC CLEANING DEVICE BY USING SPATIAL INFORMATION AND ELECTRONIC DEVICE USING SPATIAL INFORMATION FOR PERFORMING AUTOMATED CLEANING TASKS”
Applicant is encouraged to contact the examiner if an interview would be helpful in discussing and overcoming this objection.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-6, 8, 10-17, 19 and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Sinyavskiy (WO 2018144846 A1) in view of Jakhotia (US 20220095871 A1).
Regarding claim 1 Sinyavskiy discloses: A method performed by a robot cleaner (Sinyavskiy, [0012] the robot is a floor cleaning robot), the method comprising:
based on spatial information about a space including at least one object and a task that the robot cleaner is set to perform (Sinyavskiy, [0045] the robot can generate a map to autonomously navigate an environment, [0059] the robot can navigate around the object based on its known position),
selecting an object that obstructs the task from among objects located in a space corresponding to the task (Sinyavskiy, [0059] the robot can navigate around the object based its known position [0124] the sensor can detect an object obstructing the robot’s path);
[providing a user with object movement guide information as a guide for moving the object, the object movement guide information corresponding to attribute information about the object, the attribute information including a mobility level of the object and position movement cycle information of the object;]
PNG
media_image1.png
896
682
media_image1.png
Greyscale
(Figure 6a)
determining a movement path used to perform the task based on a user's response corresponding to the object movement guide information (Sinyavskiy, [0100] the path can be updated based upon whether the assist request (obstacle detected in path and corresponding request for it be removed) is resolved);
and driving the robot cleaner according to the movement path (Sinyavskiy, [0100] after the obstacle has been resolved the user has pushed a button, the robot can proceed with operation based on a determined path),
Sinyavskiy does not teach; providing a user with object movement guide information as a guide for moving the object, the object movement guide information corresponding to attribute information about the object, the attribute information including a mobility level of the object and position movement cycle information of the object;
wherein the mobility level is determined among a plurality of mobility levels in which a lowest mobility level among the plurality of mobility levels corresponds to an immovable object, at least one middle mobility level among the plurality of mobility levels corresponds to an occasionally moved movable object or an infrequently moved movable object, and a highest mobility level among the plurality of mobility levels corresponds to a frequently moved movable object.
However, in the same field of endeavor, Jakhotia teaches; providing a user with object movement guide information as a guide for moving the object, the object movement guide information corresponding to attribute information about the object, the attribute information including a mobility level of the object and position movement cycle information of the object (Jakhotia, [0015] the system uses robotic sensors to determine features which are in the vicinity of the robot, where features are structures, furniture or other objects, the features are classified as static or dynamic (attribute information) and weighted based on how static/how mobile they are (mobility level));
wherein the mobility level is determined among a plurality of mobility levels in which a lowest mobility level among the plurality of mobility levels corresponds to an immovable object (Jakhotia, [0015] the system determines environmental features, which are things in the vicinity of the robot, and determines them as static or dynamic based on how often they move or change within a set period of time, [0018] features are given a weight to describe the degree of static or dynamic they are, where [0024] the system may assign a low weight to the item which is most immobile (lowest mobility level), for example the weights may be between 0 and 100, where 0 corresponds to a completely stationary object),
at least one middle mobility level among the plurality of mobility levels corresponds to an occasionally moved movable object or an infrequently moved movable object (Jakhotia, [0015] the system determines environmental features, which are things in the vicinity of the robot, and determines them as static or dynamic based on how often they move or change within a set period of time, [0018] features are given a weight to describe the degree of static or dynamic they are, where [0112] depending on how often something moves it may not be completely static or completely dynamic, therefore the item may be assigned a percentage in between 0 and 100 (middle level) depending on how often this item moves, therefore an occasionally moved item would fall between the lowest and highest mobility levels (0 and 100)),
and a highest mobility level among the plurality of mobility levels corresponds to a frequently moved movable object (Jakhotia, [0015] the system determines environmental features, which are things in the vicinity of the robot, and determines them as static or dynamic based on how often they move or change within a set period of time, [0018] features are given a weight to describe the degree of static or dynamic they are, where [0024] the system may assign a low weight to the item which is most immobile (lowest mobility level), for example the weights may be between 0 and 100, where 100 corresponds to a highly moved object, [0016] weight is assigned based on how often an object or item is moved and encountered in a given location, for example a wall would be assumed as completely static since it encountered in the same location where a chair might be moved often and would be weighted as being extremely dynamic).
The combination of Sinyavskiy and Jakhotia would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. Sinyavskiy teaches a robot cleaner with the capacity to determine a map of the area it is cleaning and determine an obstacle in its path. Jakhotia teaches a robot cleaner with the capacity to classify objects based on how frequently the objects move in the home. The motivation to combine this capability of Jakhotia with the system of Sinyavskiy lies in that it would increase the cleaning robot’s ability to navigate an environment which is constantly changing. (Jakhotia [0002])
Regarding claim 2 the combination of Sinyavskiy and Jakhotia teaches: The method of claim 1, wherein the selecting of the object obstructing the task comprises:
obtaining a spatial map as the spatial information (Sinyavskiy, [0045] the robot can generate a map to autonomously navigate an environment);
analyzing a prediction about processing of the task by using the spatial map (Sinyavskiy, [0011] the processor is configured to learn and identify obstacles and monitor the robot through processes such as task navigation, [0007]- [0008] the robot is performing a task in an environment, and the system collects data about the robot performing the task);
and determining at least one object obstructing the task based on a result of the analyzing (Sinyavskiy, [0011] the system uses machine learning to determine an obstacle or object obstructing the task and identify it).
Regarding claim 3 the combination of Sinyavskiy and Jakhotia teaches: The method of claim 2, wherein the obtaining of the spatial map comprises obtaining the spatial map based on at least one of a first spatial map stored in the robot cleaner (Sinyavskiy, [0012] the robot is a floor cleaning robot ,[0045] the robot can generate a map to autonomously navigate an environment, the map is generated using sensors or sensor data, [0065] the data can be stored on a memory) or a second spatial map received using a communication interface of
Regarding claim 4 the combination of Sinyavskiy and Jakhotia teaches: The method of claim 2, wherein the analyzing of the prediction comprises comparing and analyzing results of predictions about the processing of the task for a plurality of movement paths that are distinguished from each other based on a position of at least one object and at least one branch point on a virtual movement path of the robot cleaner for performing the task (Sinyavskiy, [0012] the robot is a floor cleaning robot, [0120] the robots paths can be predicted through model training as well as based upon the desired task the robot will be performing, [0078]-[0079] the robot can determine if the path is blocked by an obstacle (position of an object), [0104] the robot can determine where to move to in order to clear the obstacle (branch point, where the robots path deviates from the planned path)).
Regarding claim 5 the combination of Sinyavskiy and Jakhotia teaches: The method of claim 1, wherein the providing of the object movement guide information comprises:
Identifying the attribute information about the object (Sinyavskiy, [0011] the object/obstacle is identified, [0081] robot can recognize people, animals or objects detected using the sensor, the ability to identify and differentiate obstacles indicates the ability to detect distinguishing features or attributes);
and providing the object movement guide information to the user by executing a movement request process corresponding to the attribute information about the object (Sinyavskiy, [0090] an object is detected in the path of the robot, the robot then sends an assist request to the user so the user can go assist the robot by moving the object, [0100] the assist request/event can display an instruction to the user to move the obstacle).
Regarding claim 6 the combination of Sinyavskiy and Jakhotia teaches: The method of claim 5, wherein the providing of the object movement guide information comprises transmitting, to a user terminal of the user, an analysis result obtained by analyzing a prediction about processing the task and the object movement guide information (Sinyavskiy, [0090] an object is detected in the path of the robot, the robot then sends an assist request to the user so the user can go assist the robot by moving the object (sending a result/information to the user terminal), [0100] the assist request/event can display an instruction to the user to move the obstacle, the obstacle must be detected as being in the path of the robot while is completing a task such that is interferes with the task (analogous to information about the processing of the task), following this the user receives a notification telling them to move the object (movement guide)).
Regarding claim 8 the combination of Sinyavskiy and Jakhotia teaches: The method of claim 1, wherein the determining of the movement path comprises:
based on the user’s response, identifying a moved object among selected objects (Sinyavskiy, [0100] the user presses a button in response to the “assist event” request to move an obstacle once the obstacle has been moved or the robot has been moved, after this the robot can re-localize itself to its surroundings to verify the event (obstacle/object detected) has been resolved.);
and obtaining movement path reflecting the moved object in the space corresponding to the task (Sinyavskiy, [0100], when the assist request (request to remove an obstacle) has been resolved the robot can determine a movement path to complete the task).
Regarding claim 10 the combination of Sinyavskiy and Jakhotia teaches: A non-transitory computer-readable recording medium having recorded thereon a program that, when executed by at least one processor of a robot cleaner (Sinyavskiy, [0012] the robot is a floor cleaning robot), cause the robot cleaner to perform operations, the operations comprising (Sinyavskiy, [0017] the system used non-transitory computer readable medium to execute code by a processor):
based on spatial information about a space including at least one object and a task that the robot cleaner is set to perform (Sinyavskiy, [0045] the robot can generate a map to autonomously navigate an environment, [0059] the robot can navigate around the object based on its known position),
selecting an object that obstructs the task from among objects located in a space corresponding to the task (Sinyavskiy, [0059] the robot can navigate around the object based its known position [0124] the sensor can detect an object obstructing the robot’s path);
providing a user with object movement guide information as a guide for moving the object, the object movement guide information corresponding to attribute information about the selected object, the attribute information including a mobility level of the object and position movement cycle information of the object (Jakhotia, [0015] the system uses robotic sensors to determine features which are in the vicinity of the robot, where features are structures, furniture or other objects, the features are classified as static or dynamic (attribute information) and weighted based on how static/how mobile they are (mobility level));
determining a movement path used to perform the task based on a user's response corresponding to the object movement guide information (Sinyavskiy, [0100] the path can be updated based upon whether the assist request (obstacle detected in path and corresponding request for it be removed) is resolved);
and driving the robot cleaner according to the movement path (Sinyavskiy, [0100] after the obstacle has been resolved the user has pushed a button, the robot can proceed with operation based on a determined path),
wherein the mobility level is determined among a plurality of mobility levels in which a lowest mobility level among the plurality of mobility levels corresponds to an immovable object (Jakhotia, [0015] the system determines environmental features, which are things in the vicinity of the robot, and determines them as static or dynamic based on how often they move or change within a set period of time, [0018] features are given a weight to describe the degree of static or dynamic they are, where [0024] the system may assign a low weight to the item which is most immobile (lowest mobility level), for example the weights may be between 0 and 100, where 0 corresponds to a completely stationary object),
at least one middle mobility level among the plurality of mobility levels corresponds to an occasionally moved movable object or an infrequently moved movable object (Jakhotia, [0015] the system determines environmental features, which are things in the vicinity of the robot, and determines them as static or dynamic based on how often they move or change within a set period of time, [0018] features are given a weight to describe the degree of static or dynamic they are, where [0112] depending on how often something moves it may not be completely static or completely dynamic, therefore the item may be assigned a percentage in between 0 and 100 (middle level) depending on how often this item moves, therefore an occasionally moved item would fall between the lowest and highest mobility levels (0 and 100)),
and a highest mobility level among the plurality of mobility levels corresponds to a frequently moved movable object (Jakhotia, [0015] the system determines environmental features, which are things in the vicinity of the robot, and determines them as static or dynamic based on how often they move or change within a set period of time, [0018] features are given a weight to describe the degree of static or dynamic they are, where [0024] the system may assign a low weight to the item which is most immobile (lowest mobility level), for example the weights may be between 0 and 100, where 100 corresponds to a highly moved object, [0016] weight is assigned based on how often an object or item is moved and encountered in a given location, for example a wall would be assumed as completely static since it encountered in the same location where a chair might be moved often and would be weighted as being extremely dynamic).
The combination of Sinyavskiy and Jakhotia would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. Sinyavskiy teaches a robot cleaner with the capacity to determine a map of the area it is cleaning and determine an obstacle in its path. Jakhotia teaches a robot cleaner with the capacity to classify objects based on how frequently the objects move in the home. The motivation to combine this capability of Jakhotia with the system of Sinyavskiy lies in that it would increase the cleaning robot’s ability to navigate an environment which is constantly changing. (Jakhotia [0002])
Regarding claim 11 the combination of Sinyavskiy and Jakhotia teaches: A robot cleaner using spatial information, the robot cleaner comprising (Sinyavskiy, [0012] the robot is a floor cleaning robot):
(Sinyavskiy, [0061] the system has a memory);
a sensor (Sinyavskiy, [0007] the system has at least one sensor the robot uses to generate data about the environment); and
one or more processors coupled to the memory and the (Sinyavskiy, [0017] the system used non-transitory computer readable medium to execute code by a processor)
wherein the instructions, when executed by the one or more processors individually or collectively cause the robot cleaner to (Sinyavskiy, [0017] the system used non-transitory computer readable medium to execute code by a processor):
based on spatial information, obtained via the sensor, about a space including at least one object and a task that the robot cleaner is set to perform (Sinyavskiy, [0045] the robot can generate a map to autonomously navigate an environment, [0059] the robot can navigate around the object based its known position),
select an object that obstructs the task from among objects located in a space corresponding to the task (Sinyavskiy, [0059] the robot can navigate around the object based its known position [0124] the sensor can detect an object obstructing the robot’s path),
provide a user with object movement guide information as a guide for moving the object, the object movement guide information corresponding to attribute information about the object, the attribute information including a mobility level of the object and position movement cycle information of the object (Jakhotia, [0015] the system uses robotic sensors to determine features which are in the vicinity of the robot, where features are structures, furniture or other objects, the features are classified as static or dynamic (attribute information) and weighted based on how static/how mobile they are (mobility level)),
determine a movement path used to perform the task based on a user's response corresponding to the object movement guide information (Sinyavskiy, [0100] the path can be updated based upon whether the assist request (obstacle detected in path and corresponding request for it be removed) is resolved),
and drive the robot cleaner according to the determined movement path (Sinyavskiy, [0100] after the obstacle has been resolved the user has pushed a button, the robot can proceed with operation based on a determined path),
wherein the mobility level is determined among a plurality of mobility levels in which a lowest mobility level among the plurality of mobility levels corresponds to an immovable object (Jakhotia, [0015] the system determines environmental features, which are things in the vicinity of the robot, and determines them as static or dynamic based on how often they move or change within a set period of time, [0018] features are given a weight to describe the degree of static or dynamic they are, where [0024] the system may assign a low weight to the item which is most immobile (lowest mobility level), for example the weights may be between 0 and 100, where 0 corresponds to a completely stationary object),
at least one middle mobility level among the plurality of mobility levels corresponds to an occasionally moved movable object or an infrequently moved movable object (Jakhotia, [0015] the system determines environmental features, which are things in the vicinity of the robot, and determines them as static or dynamic based on how often they move or change within a set period of time, [0018] features are given a weight to describe the degree of static or dynamic they are, where [0112] depending on how often something moves it may not be completely static or completely dynamic, therefore the item may be assigned a percentage in between 0 and 100 (middle level) depending on how often this item moves, therefore an occasionally moved item would fall between the lowest and highest mobility levels (0 and 100)),
and a highest mobility level among the plurality of mobility levels corresponds to a frequently moved movable object (Jakhotia, [0015] the system determines environmental features, which are things in the vicinity of the robot, and determines them as static or dynamic based on how often they move or change within a set period of time, [0018] features are given a weight to describe the degree of static or dynamic they are, where [0024] the system may assign a low weight to the item which is most immobile (lowest mobility level), for example the weights may be between 0 and 100, where 100 corresponds to a highly moved object, [0016] weight is assigned based on how often an object or item is moved and encountered in a given location, for example a wall would be assumed as completely static since it encountered in the same location where a chair might be moved often and would be weighted as being extremely dynamic).
The combination of Sinyavskiy and Jakhotia would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. Sinyavskiy teaches a robot cleaner with the capacity to determine a map of the area it is cleaning and determine an obstacle in its path. Jakhotia teaches a robot cleaner with the capacity to classify objects based on how frequently the objects move in the home. The motivation to combine this capability of Jakhotia with the system of Sinyavskiy lies in that it would increase the cleaning robot’s ability to navigate an environment which is constantly changing. (Jakhotia [0002])
Regarding claim 12 the combination of Sinyavskiy and Jakhotia teaches: The robot cleaner of claim 11, wherein the instructions, when executed by the one or more processors individually or collectively further cause the robot cleaner to (Sinyavskiy, [0012] the robot is a floor cleaning robot,[0017] the system used non-transitory computer readable medium to execute code by a processor):
obtain a spatial map as the spatial information (Sinyavskiy, [0045] the robot can generate a map to autonomously navigate an environment);
analyze a prediction about processing the task by using the spatial map (Sinyavskiy, [0011] the processor is configured to learn and identify obstacles and monitor the robot through processes such as task navigation, [0007]- [0008] the robot is performing a task in an environment, and the system collects data about the robot performing the task);
and determine at least one object obstructing the task, based on a result of the analyzing (Sinyavskiy, [0011] the system uses machine learning to determine an obstacle or object obstructing the task and identify it).
Regarding claim 13 the combination of Sinyavskiy and Jakhotia teaches; The robot cleaner of claim 11, wherein the instructions, when executed by the one or more processors individually or collectively further cause the robot cleaner to (Sinyavskiy, [0012] the robot is a floor cleaning robot, [0017] the system used non-transitory computer readable medium to execute code by a processor):
obtain the spatial map based on at least one of a first spatial map stored in the memory (Sinyavskiy, [0045] the robot can generate a map to autonomously navigate an environment, the map is generated using sensors or sensor data, [0065] the data can be stored on a memory) or a second spatial map received sing a communication interface of
Regarding claim 14 the combination of Sinyavskiy and Jakhotia teaches; The robot cleaner of claim 11, wherein the instructions, when executed by the one or more processors individually or collectively further cause the robot cleaner to (Sinyavskiy, [0012] the robot is a floor cleaning robot, [0017] the system used non-transitory computer readable medium to execute code by a processor):
compare and analyze results of predictions about the processing of the task for a plurality of movement paths that are distinguished from each other based on a position of at least one object and at least one branch point on a virtual movement path of the robot cleaner for performing the task (Sinyavskiy, [0120] the robots paths can be predicted through model training as well as based upon the desired task the robot will be performing, [0078]-[0079] the robot can determine if the path is blocked by an obstacle (position of an object), [0104] the robot can determine where to move to in order to clear the obstacle (branch point, where the robots path deviates from the planned path)).
Regarding claim 15 the combination of Sinyavskiy and Jakhotia teaches; The robot cleaner of claim 12 (Sinyavskiy, [0012] the robot is a floor cleaning robot), wherein the spatial map comprises a plurality of layers based on the attribute information about the object ([0057]-[0058] of applicant’s spec defines the map layers as having a base layer, a semantic layer and a real time layer, which includes position information about objects, semantic classification and structures of the room/building, Sinyavskiy figures 6A-6C show a map having object positions, alerts, and environmental structure which is analogous to the layers of the applicant’s specification).
Regarding claim 16 the combination of Sinyavskiy and Jakhotia teaches; The robot cleaner of claim 11, wherein the instructions, when executed by the one or more processors individually or collectively further cause the robot cleaner to (Sinyavskiy, [0012] the robot is a floor cleaning robot,[0017] the system used non-transitory computer readable medium to execute code by a processor):
Identify the attribute information about the object (Sinyavskiy, [0011] the object/obstacle is identified, [0081] robot can recognize people, animals or objects detected using the sensor, the ability to identify and differentiate obstacles indicates the ability to detect distinguishing features or attributes);
and provide the object movement guide information to the user by executing a movement request process corresponding to the attribute information about the object (Sinyavskiy, [0090] an object is detected in the path of the robot, the robot then sends an assist request to the user so the user can go assist the robot by moving the object, [0100] the assist request/event can display an instruction to the user to move the obstacle).
Regarding claim 17 the combination of Sinyavskiy and Jakhotia teaches; The robot cleaner of claim 16, further comprising: a communication interface, wherein the instructions, when executed by the one or more processors individually or collectively, further cause the robot cleaner to transmit, via the communication interface to a user terminal of the user (Sinyavskiy, [0012] the robot is a floor cleaning robot,[0017] the system used non-transitory computer readable medium to execute code by a processor), an analysis result obtained by analyzing a prediction about processing the task and the object movement guide information (Sinyavskiy, [0090] an object is detected in the path of the robot, the robot then sends an assist request to the user so the user can go assist the robot by moving the object (sending a result/information to the user terminal), [0100] the assist request/event can display an instruction to the user to move the obstacle, the obstacle must be detected as being in the path of the robot while is completing a task such that is interferes with the task (analogous to information about the processing of the task), following this the user receives a notification telling them to move the object (movement guide)).
Regarding claim 19 the combination of Sinyavskiy and Jakhotia teaches; The robot cleaner of claim 11, wherein the instructions, when executed by the one or more processors individually or collectively further cause the robot cleaner to:
based on the user’s response, identify a moved object among selected objects (Sinyavskiy, [0100] the user presses a button in response to the “assist event” request to move an obstacle once the obstacle has been moved or the robot has been moved, after this the robot can re-localize itself to its surroundings to verify the event (obstacle/object detected) has been resolved.);
and obtain a movement path reflecting the moved object in the space corresponding to the task (Sinyavskiy, [0100], when the assist request (request to remove an obstacle) has been resolved the robot can determine a movement path to complete the task).
Regarding claim 21, the combination of Sinyavskiy and Jakhotia teaches; The method claim 1,
wherein the mobility level of the object is determined by applying objective characteristics of the object to a predetermined classification criterion for evaluating mobility (Jakhotia, [0015] the system uses robotic sensors to determine features which are in the vicinity of the robot, where features are structures, furniture or other objects, the features are classified as static or dynamic (attribute information) and weighted based on how static/how mobile they are (mobility level), [0035] the objects are classified based on how often they appear in the same position and compared to a threshold),
The combination of Sinyavskiy and Jakhotia would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. Sinyavskiy teaches a robot cleaner with the capacity to determine a map of the area it is cleaning and determine an obstacle in its path. Jakhotia teaches a robot cleaner with the capacity to classify objects based on how frequently the objects move in the home. The motivation to combine this capability of Jakhotia with the system of Sinyavskiy lies in that it would increase the cleaning robot’s ability to navigate an environment which is constantly changing. (Jakhotia [0002])
Claims 7 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Sinyavskiy (WO 2018144846 A1) in view of Jakhotia (US 20220095871 A1) and in further view of Choi (US 10852729 B2).
Regarding claim 7 the combination of Sinyavskiy and Jakhotia fails to teach;
The method of claim 5, wherein the providing of the object movement guide information comprises: selecting, on a three-dimensional (3D) spatial map of a region where the object is located, candidate positions to which the object is to be moved;
obtaining, for each candidate position, an image showing a state in which the object is moved to a corresponding candidate position; evaluating the image via an image evaluation model by inputting the image into the image evaluation model;
and transmitting, to a user terminal of the user, the object movement guide information according to a result of the evaluating of the image.
However, in the same field of endeavor, Choi teaches; selecting, on a three-dimensional (3D) spatial map of a region where the object is located, candidate positions to which the object is to be moved (Choi, Column 19, lines 40-50, the robot detects the location of obstacles which can be moved, Column 20, lines 28-41, the robot can provide the user a map in which positions where the obstacles can be moved are displayed for the user to select);
obtaining, for each candidate position, an image showing a state in which the object is moved to a corresponding candidate position (Choi, Figure 28 shows candidate positions for the obstacle/object to be moved on a map, Column 20 lines 28-49 the robot will move the object to the selected candidate position and the map displays this information on the interface for the user);
PNG
media_image2.png
618
446
media_image2.png
Greyscale
(Choi, Figure 28)
evaluating the image via an image evaluation model by inputting the image into the image evaluation model (Choi, Column 21, lines 52-63, the robot stores and obtains object/obstacle position and movement information based upon images, which is analogous to evaluating an image using an image recognition model);
and transmitting, to a user terminal of the user, the object movement guide information according to a result of the evaluating of the image (Choi, Figure 28 shows candidate positions for the obstacle/object to be moved on a map, Column 20 lines 28-49 the robot will move the object to the selected candidate position and the map displays this information on the interface for the user, the positions are determined based upon images).
The combination of Sinyavskiy, Jakhotia and Choi would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. The system of Sinyavskiy teaches a robot cleaner which uses machine learning to detect obstacles and signal the user to assist with moving an obstacle so the device can clean. The system of Jakhotia teaches a method of increased navigation ability using dynamic object classification and weighting. The system of Choi teaches a robot cleaner which can detect obstacles, determine new locations for them and move the obstacles or have the user move them. The combination of the systems of Sinyavskiy and Jakhotia with the system of Choi would allow a robot cleaner to prompt the relocation of obstacles and provide a set of candidate positions for more effective cleaning of a space because the system can determine a more ideal location for an object such that it is out of the way. (Choi, Columns 19 and 20)
Regarding claim 18 the combination of Sinyavskiy, Jakhotia and Choi teaches; The robot cleaner of claim 16, further comprising:
a communication interface, wherein the instructions, when executed by the one or more processors individually or collectively, further cause the robot cleaner to (Sinyavskiy, [0012] the robot is a floor cleaning robot, [0017] the system used non-transitory computer readable medium to execute code by a processor):
select, on a three-dimensional (3D) spatial map of a region where (Choi, Column 19, lines 40-50, the robot detects the location of obstacles which can be moved, Column 20, lines 28-41, the robot can provide the user a map in which positions where the obstacles can be moved are displayed for the user to select);
obtain, for each candidate position, an image showing a state in which the object is moved to a corresponding candidate position (Choi, Figure 28 shows candidate positions for the obstacle/object to be moved on a map, Column 20 lines 28-49 the robot will move the object to the selected candidate position and the map displays this information on the interface for the user);
PNG
media_image2.png
618
446
media_image2.png
Greyscale
(Choi, Figure 28)
evaluate the image via an image evaluation model by inputting the image into the image evaluation model (Choi, Column 21, lines 52-63, the robot stores and obtains object/obstacle position and movement information based upon images, which is analogous to evaluating an image using an image recognition model);
and transmit, to a user terminal of the user, the object movement guide information according to a result of the evaluating of the image (Choi, Figure 28 shows candidate positions for the obstacle/object to be moved on a map, Column 20 lines 28-49 the robot will move the object to the selected candidate position and the map displays this information on the interface for the user, the positions are determined based upon images).
The combination of Sinyavskiy, Jakhotia and Choi would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. The system of Sinyavskiy teaches a robot cleaner which uses machine learning to detect obstacles and signal the user to assist with moving an obstacle so the device can clean. The system of Jakhotia teaches a method of increased navigation ability using dynamic object classification and weighting. The system of Choi teaches a robot cleaner which can detect obstacles, determine new locations for them and move the obstacles or have the user move them. The combination of the systems of Sinyavskiy and Jakhotia with the system of Choi would allow a robot cleaner to prompt the relocation of obstacles and provide a set of candidate positions for more effective cleaning of a space because the system can determine a more ideal location for an object such that it is out of the way. (Choi, Columns 19 and 20)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. For a listing of analogous art as cited by the examiner please see the attached PTO-892 Notice of References Cited form.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JORDAN M ELLIOTT whose telephone number is (703)756-5463. The examiner can normally be reached M-F 8AM-5PM 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, Emily Terrell can be reached at (571) 270-3717. 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.
/J.M.E./Examiner, Art Unit 2666 /EMILY C TERRELL/Supervisory Patent Examiner, Art Unit 2666
Prosecution Insights