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 .
DETAILED ACTION
Status of Claims
The following is a non-final office action in response to the preliminary amendment filed on 08/28/2025.
Claims 1-9 are either amended directly or via a claim they depend from.
Claims 10-11 are canceled.
Claims 1-9 are rejected.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 08/25/2025 was filed. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Objection to the Specification
The disclosure is objected to because of the following informalities:
Paragraph [0004], Line 28, should grammatically read, “a method in which only a leader grasps,” for clarity.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-9 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation "the another mobile body" in Lines 8-9. There is insufficient antecedent basis for this limitation in the claim. Claims 2-3 are rejected based upon their dependency on claim 1. For the purposes of examination, the it will be assumed “the another mobile body” is intended to refer to “the follower mobile body.”
Claim 1 recites the limitation "the mobile body" in Line 21. It is unclear whether this limitation is intended to refer to the “leader mobile body,” “follower mobile body,” or either of them. Claims 2-3 are rejected based upon their dependency on claim 1. For the purposes of examination, the it will be assumed “the mobile body” is intended to refer to either the “leader mobile body” or “follower mobile body.”
Claim 4 recites the limitation "the another mobile body" in Line 5. There is insufficient antecedent basis for this limitation in the claim. Claims 5-6 are rejected based upon their dependency on claim 4. For the purposes of examination, the it will be assumed “the another mobile body” is intended to refer to “the follower mobile body.”
Claim 4 recites the limitation "the mobile body" in Line 14. It is unclear whether this limitation is intended to refer to the “leader mobile body,” “follower mobile body,” or either of them. Claims 5-6 are rejected based upon their dependency on claim 4. For the purposes of examination, the it will be assumed “the mobile body” is intended to refer to either the “leader mobile body” or “follower mobile body.”
Claim 7 recites the limitation "the another mobile body" in Line 6. There is insufficient antecedent basis for this limitation in the claim. Claims 8-9 are rejected based upon their dependency on claim 7. For the purposes of examination, the it will be assumed “the another mobile body” is intended to refer to “the follower mobile body.”
Claim 7 recites the limitation "the mobile body" in Line 15. It is unclear whether this limitation is intended to refer to the “leader mobile body,” “follower mobile body,” or either of them. Claims 8-9 are rejected based upon their dependency on claim 7. For the purposes of examination, the it will be assumed “the mobile body” is intended to refer to either the “leader mobile body” or “follower mobile body.”
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 1-9 are rejected under 35 U.S.C. 103 as being unpatentable over Paschall et al., (US 11,994,874 B1, hereinafter Paschall) in view of Park et al. (US 2025/0348090 A1, hereinafter Park)
Claim 1 Discloses: (Currently Amended)
“An information processing apparatus comprising: at least one memory storing instructions; and at least one processor configured to execute the instructions to:”
Paschall teaches, (Abstract, Lines 1-2) “Autonomous mobile robots (AMRs) having adaptive safety systems [which] may operate individually or as part of a convoy,” wherein, (Page 28, Column 29, Lines 58-61) “the AMR control system 1100 includes one or more processors 1102, coupled to a non-transitory computer readable storage medium 1120 via an input/output (I/O) interface 1110,” and that, (Page 28, Column 30, Lines 13-15) “The non-transitory computer readable storage medium 1120 may be configured to store executable instructions, applications, drivers, and/or data, such as AMR data.”
“set a path of each mobile body in a formation controlled in such a way that a leader mobile body makes a follower mobile body follow;”
Paschall teaches, (Page 19, Column 11, Lines 11-13) “During convoy operations, a first, or leader, AMR 305 may modify one or more movement characteristics to operate as a leader of the convo e.g., modify speed, direction, or path,” and further teaches, (Page 14, Column 2, Lines 37-41) “Using the adaptive safety systems as further described herein to enable convoy operations, two or more autonomous mobile robots, e.g., including a leader autonomous mobile robot and one or more follower autonomous mobile robots.”
“set virtual barriers indicating safe regions of the mobile bodies;”
Paschall teaches that, (Abstract, Lines 3-4) “an AMR may determine a safety zone,” and, (Page 14, Column 2, Lines 64-67 & Page 15, Column 3, Lines 1-3) “In addition, the first and second AMRs may navigate within structured areas or fields, e.g., areas having identifiers, codes, or other markings associated with various locations that aid navigation and location determination, or within unstructured areas or fields, e.g., areas without identifiers, codes, or other markings associated with various locations.”
“measure relative coordinates with the another mobile body and calculating a position of the follower mobile body recognized by the leader mobile body;”
Paschall teaches, (Page 22, Column 18, Lines 34-44) “the leader AMR may modify one or more movement characteristics in order to facilitate formation of the convoy that will follow the leader AMR. For example, the one or more movement characteristics may include modifying speed, stopping, accelerating, decelerating, changing direction, turning, adjusting a path, rerouting, maintaining defined separation distances, and/or other modifications to movement characteristics. In some example embodiments, a leader AMR may slow or stop in order to allow one or more follower AMRs to catch up to and follow the leader AMR,” and that, (Page 18, Column 9, Lines 14-16) “the safety system controller 233 may process the data associated with detected objects, which may include transposing the data to a desired coordinate system.”
Paschall additionally teaches, (Page 14, Column 2, Lines 44-48) “The one or more follower autonomous mobile robots may substantially continuously or intermittently detect the leader, or a preceding, autonomous mobile robot in order to maintain the convoy operations.”
“transmit and receive, according to a request,”
Paschall teaches, (Page 22, Column 18, Lines 10-11) “FIG. 7 is a flow diagram illustrating an example convoy formation process 700,” wherein, (Page 22, Column 18, Lines 21-25) “the control system may send or transmit instructions or commands to the AMRs to form the convoy with the determined movement characteristics, as well as data or information, e.g., identifier or codes, associated one or more other AMRs that are to form the convoy,” and that, (Page 23, Column 19, Lines 8-10) “In addition, each follower AMR may receive data or information associated with the leader or preceding AMR that the follower AMR is to detect, identify, and follow.”
“the paths and the virtual barriers,”
Paschall teaches, (Page 23, Columns 19 Line 66-67 & Page 23 Column 20, Lines 1-8) “the detected identifier does match the expected identifier that the follower AMR is to identify and follow, then the process 700 may continue with muting, by the controller of the follower AMR, a forward portion of a safety zone of the follower AMR, as at 712. For example, a portion of the safety zone of the follower AMR may be selectively muted to permit or allow a portion of the leader or preceding AMR, and its associated identifier, within the portion of the safety zone, e.g., toward a forward movement direction of the follower AMR.”
“or further positions of the mobile bodies;”
Paschall teaches, (Page 23, Column 20, lines 25-32) “The process 700 may proceed with adjusting, by a controller of a leader AMR, movement characteristics for convoy operation, as at 714. For example, based on the received instructions to form a convoy with one or more other AMRs and based on a determination that the AMRs have completed formation of the convoy, the leader AMR may modify one or more movement characteristics in order to lead the convoy.”
“store set paths; store the set virtual barriers;”
Paschall teaches, (Page 30, Column 34, Lines 57-67 & Page 31, Column 35, Lines 1-3) “The data storage 1235 may include various data stores for maintaining data related to systems, operations, or processes described herein, such as facility or environment data including characteristics of the environment, AMR data, identifier or code data, sensor data, safety zone data, separation distance data, detected object data, navigation data, drive mechanism data, path or destination data, movement characteristics data including position, speed, acceleration, weight, load, planned path, destination, or other movement characteristics, lift mechanism data, other sensor data, material handling equipment or apparatus, upstream systems, stations, or processes, downstream systems, stations, or processes, etc.”
“predict a maximum value of displacement between a self-recognition position and an actual position; and estimate self-recognition position,”
Paschall does not explicitly teach the preceding limitations related to predicting a maximum value of displacement between a self-recognition position and an actual position.
Park does teach the preceding limitations.
Park teaches, (Abstract, Lines 1-2) “an unmanned aerial vehicle formation control system,” in reference to description of scenario present in the prior art wherein, (Paragraph [0009], Lines 1-5) “in a formation flight (A1) of agricultural unmanned aerial vehicles, each agricultural unmanned aerial vehicle flies in formation based on the provided location data, so that a control overlap zone 10 or a no-control zone 20 occurs,” the reference which is relevant to the applicant’s disclosure due to its teachings of measuring the maximum value of displacement between a self-recognition position and an actual position in the context of a vehicle platoon.
Park teaches a, (Abstract, Lines 4-15) “system including a data processing unit that receives the location data and distance data of the unmanned aerial vehicles and provides the received location data and distance data to other unmanned aerial vehicles belonging to a formation of the unmanned aerial vehicles; a formation alignment unit that selectively uses the location data and the distance data to align the formation of the unmanned aerial vehicles; and a formation error determination unit that calculates an overall formation error value due to formation alignment mismatch based on the location data of the unmanned aerial vehicle, and compares the formation error value with a preset allowable threshold value to determine whether a formation error of the unmanned aerial vehicle has occurred.”
“requesting communication in a case where it is determined that there is a possibility that the mobile body is outside the virtual barrier in consideration of the maximum value of the displacement,”
Park teaches, (Paragraph [0066]) “the formation control system 200 may compare the overall formation error value with a preset allowable threshold value to determine whether a formation error has occurred. When it is determined that a formation error has occurred, the formation control system 200 may realign the leader unmanned aerial vehicle 110 and the follower unmanned aerial vehicle 120 based on location data. That is, when it is determined that a formation error has occurred, the formation control system 200 may switch from controlling a formation based on distance data to controlling the formation based on location data.” Examiner is interpreting the switching of controlling a formation based on distance data to controlling the formation based on location data as part of a realignment operating as an example of the system requesting communication under broadest reasonable interpretation. The interpretation is derived from Applicant’s specification, which reads, (Paragraph [0011], Lines 7-8) “transmitting and receiving, according to a request, the paths and the virtual barriers, or further positions of the mobile bodies,” the preceding teachings being interpreted as an example of transmitting and receiving further position of the mobile bodies.
“and update the self-recognition position.”
Park teaches, (Paragraphs [0089-0090]) “when a formation error has occurred, the formation alignment unit 230 may switch the unmanned aerial vehicle 100, which has been controlled based on distance data, to be controlled based on location data,” and that, “Additionally, the formation alignment unit 230 may realign the unmanned aerial vehicle 100 based on location data, and then switch back to controlling the unmanned aerial vehicle 100 based on distance data,” wherein, (Paragraph [0055], Lines 4-6) “the leader unmanned aerial vehicle 110 may measure distance data from the follower unmanned aerial vehicle 120 adjacent thereto using the distance measurement sensor.”
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to combine the autonomous mobile robot platooning system which is capable of maintaining a separation difference between robots within a desired region all taught by Paschall, with the explicit teachings of predicting a maximum value of displacement between a self-recognition position and an actual position in context of a group of leader/follower robots as taught by Park, in order to yield predictable results.
Combining the references would yield the benefits of minimizing accumulated error during the travel of a vehicle platoon by comparing the desired vs actual locations of the vehicle, the error of which could introduce collision or entrance of the vehicles into unwanted areas. As Park describes, (Paragraph [0031]) “according to an embodiment of the present disclosure, a formation control system may perform formation alignment based on location data of unmanned aerial vehicles, and then control a formation form to be maintained constant based on distance data of the unmanned aerial vehicles, thereby minimizing formation error accumulation that may occur in location data-based formation control as in the related art.”
Claim 2 Discloses: (Currently Amended)
“The information processing apparatus according to claim 1, wherein the one or more processors further:
Paschall does not explicitly teach resetting the displacement to 0 after a timing at which the self-recognition position is updated and a timing at which the position of the follower mobile body is calculated.
Park does teach the preceding limitations.
Park teaches, (Paragraph [0058], Lines 1-2) “the follower unmanned aerial vehicle 120 may measure location data using the location measurement sensor,” and that (Paragraph [0079]) “the formation error determination unit 220 may calculate a formation error value using the location data of the unmanned aerial vehicle 100 received in real time and ideal location data of the unmanned aerial vehicle 100 at the corresponding point in time. For example, the formation error determination unit 220 may calculate a difference between the real-time measured location data of the leader unmanned aerial vehicle and the follower unmanned aerial vehicle included in the unmanned aerial vehicle 100 and the ideal location data of each of the leader unmanned aerial vehicle and the follower unmanned aerial vehicle at that point in time as a formation error value. At this time, the formation error value may be derived for each of the leader unmanned aerial vehicle and the follower unmanned aerial vehicle.”
Park additionally teaches, (Paragraph [0088]) “when the formation error determination unit 230 determines that a formation error has occurred, the formation alignment unit 230 may realign the formation of the unmanned aerial vehicle 100 based on the location data of the unmanned aerial vehicle 100,” and that, (Paragraph [0090]) “the formation alignment unit 230 may realign the unmanned aerial vehicle 100 based on location data, and then switch back to controlling the unmanned aerial vehicle 100 based on distance data.” Note: once the formulation error surpassed a threshold as in cited Paragraph [0088], realignment may occur. During the realignment, the system of Park switches the manner in which it measures location to “distance data” to start a new and remove the measurement error.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to combine the autonomous mobile robot platooning system which is capable of maintaining a separation difference between robots within a desired region as taught by Paschall, with the explicit teachings of predicting a maximum value of displacement between a self-recognition position and an actual position in context of a group of leader/follower robots and subsequent time based alignment iteration which resets the displacement to zero as taught by Park, in order to yield predictable results.
Combining the references would yield the benefits of minimizing accumulated error over time during the travel of a vehicle platoon by comparing the desired vs actual locations of the vehicle, the error of which could introduce collision or entrance of the vehicles into unwanted areas. As Park describes, (Paragraph [0031]) “according to an embodiment of the present disclosure, a formation control system may perform formation alignment based on location data of unmanned aerial vehicles, and then control a formation form to be maintained constant based on distance data of the unmanned aerial vehicles, thereby minimizing formation error accumulation that may occur in location data-based formation control as in the related art.”
Claim 3 Discloses: (Currently Amended)
“The information processing apparatus according to claim 1, wherein the one or more processors further:
Paschall does not explicitly teach updating the self-recognition position when the leader mobile body receives a self-position.
Park does teach the preceding limitations.
Park teaches, (Paragraph [0055]) “the leader unmanned aerial vehicle 110 may perform a formation flight based on location data acquired by the location measurement sensor. Furthermore, the leader unmanned aerial vehicle 110 may measure distance data from the follower unmanned aerial vehicle 120 adjacent thereto using the distance measurement sensor. The leader unmanned aerial vehicle 110 may share the measured location data and distance data with the follower unmanned aerial vehicle 110 through the formation control system 200,” and that (Paragraph [0079]) “the formation error determination unit 220 may calculate a formation error value using the location data of the unmanned aerial vehicle 100 received in real time and ideal location data of the unmanned aerial vehicle 100 at the corresponding point in time. For example, the formation error determination unit 220 may calculate a difference between the real-time measured location data of the leader unmanned aerial vehicle and the follower unmanned aerial vehicle included in the unmanned aerial vehicle 100 and the ideal location data of each of the leader unmanned aerial vehicle and the follower unmanned aerial vehicle at that point in time as a formation error value. At this time, the formation error value may be derived for each of the leader unmanned aerial vehicle and the follower unmanned aerial vehicle.”
Park additionally teaches, (Paragraph [0088]) “when the formation error determination unit 230 determines that a formation error has occurred, the formation alignment unit 230 may realign the formation of the unmanned aerial vehicle 100 based on the location data of the unmanned aerial vehicle 100,” and that, (Paragraph [0090]) “the formation alignment unit 230 may realign the unmanned aerial vehicle 100 based on location data, and then switch back to controlling the unmanned aerial vehicle 100 based on distance data.”
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to combine the autonomous mobile robot platooning system which is capable of maintaining a separation difference between robots within a desired region as taught by Paschall, with the explicit teachings of predicting a maximum value of displacement between a self-recognition position and an actual position in context of a group of leader/follower robots and subsequent time based alignment iteration as taught by Park, in order to yield predictable results.
Combining the references would yield the benefits of minimizing accumulated error over time during the travel of a vehicle platoon by comparing the desired vs actual locations of the vehicle, the error of which could introduce collision or entrance of the vehicles into unwanted areas. As Park describes, (Paragraph [0031]) “according to an embodiment of the present disclosure, a formation control system may perform formation alignment based on location data of unmanned aerial vehicles, and then control a formation form to be maintained constant based on distance data of the unmanned aerial vehicles, thereby minimizing formation error accumulation that may occur in location data-based formation control as in the related art.”
Claim 4 Discloses: (Original)
“A control method by a computer, the control method comprising:”
Paschall teaches, (Abstract, Lines 1-2) “Autonomous mobile robots (AMRs) having adaptive safety systems [which] may operate individually or as part of a convoy,” which further, (Page 14, Column 1, Lines 67 & Page 14, Column 2, Lines 1-3) are directed to autonomous mobile robots having adaptive safety systems to initiate, form, perform, adjust, and terminate convoy operations, and corresponding methods related to convoy operations,” and further teaches that, (Page 28, Column 29, Lines 58-61) “the AMR control system 1100 includes one or more processors 1102, coupled to a non-transitory computer readable storage medium 1120 via an input/output (I/O) interface 1110.”
“setting a path of each mobile body in a formation controlled in such a way that a leader mobile body makes a follower mobile body follow;”
Paschall teaches, (Page 19, Column 11, Lines 11-13) “During convoy operations, a first, or leader, AMR 305 may modify one or more movement characteristics to operate as a leader of the convo e.g., modify speed, direction, or path,” and further teaches, (Page 14, Column 2, Lines 37-41) “Using the adaptive safety systems as further described herein to enable convoy operations, two or more autonomous mobile robots, e.g., including a leader autonomous mobile robot and one or more follower autonomous mobile robots.”
“setting virtual barriers indicating safe regions of the mobile bodies;”
Paschall teaches, (Abstract, Lines 3-4) “an AMR may determine a safety zone,” and, (Page 14, Column 2, Lines 64-67 & Page 15, Column 3, Lines 1-3) “In addition, the first and second AMRs may navigate within structured areas or fields, e.g., areas having identifiers, codes, or other markings associated with various locations that aid navigation and location determination, or within unstructured areas or fields, e.g., areas without identifiers, codes, or other markings associated with various locations.”
“measuring relative coordinates with the another mobile body and calculating a position of the follower mobile body recognized by the leader mobile body;”
Paschall teaches, (Page 22, Column 18, Lines 34-44) “the leader AMR may modify one or more movement characteristics in order to facilitate formation of the convoy that will follow the leader AMR. For example, the one or more movement characteristics may include modifying speed, stopping, accelerating, decelerating, changing direction, turning, adjusting a path, rerouting, maintaining defined separation distances, and/or other modifications to movement characteristics. In some example embodiments, a leader AMR may slow or stop in order to allow one or more follower AMRs to catch up to and follow the leader AMR,” and that, (Page 18, Column 9, Lines 14-16) “the safety system controller 233 may process the data associated with detected objects, which may include transposing the data to a desired coordinate system.”
Paschall additionally teaches, (Page 14, Column 2, Lines 44-48) “The one or more follower autonomous mobile robots may substantially continuously or intermittently detect the leader, or a preceding, autonomous mobile robot in order to maintain the convoy operations.”
“transmitting and receiving, according to a request,”
Paschall teaches, (Page 22, Column 18, Lines 10-11) “FIG. 7 is a flow diagram illustrating an example convoy formation process 700,” wherein, (Page 22, Column 18, Lines 21-25) “the control system may send or transmit instructions or commands to the AMRs to form the convoy with the determined movement characteristics, as well as data or information, e.g., identifier or codes, associated one or more other AMRs that are to form the convoy,” and that, (Page 23, Column 19, Lines 8-10) “In addition, each follower AMR may receive data or information associated with the leader or preceding AMR that the follower AMR is to detect, identify, and follow.”
“the paths and the virtual barriers,”
Paschall teaches, (Page 23, Columns 19 Line 66-67 & Page 23 Column 20, Lines 1-8) “the detected identifier does match the expected identifier that the follower AMR is to identify and follow, then the process 700 may continue with muting, by the controller of the follower AMR, a forward portion of a safety zone of the follower AMR, as at 712. For example, a portion of the safety zone of the follower AMR may be selectively muted to permit or allow a portion of the leader or preceding AMR, and its associated identifier, within the portion of the safety zone, e.g., toward a forward movement direction of the follower AMR.”
“or further positions of the mobile bodies;”
Paschall teaches, (Page 23, Column 20, lines 25-32) “The process 700 may proceed with adjusting, by a controller of a leader AMR, movement characteristics for convoy operation, as at 714. For example, based on the received instructions to form a convoy with one or more other AMRs and based on a determination that the AMRs have completed formation of the convoy, the leader AMR may modify one or more movement characteristics in order to lead the convoy.”
“storing the set paths; storing the set virtual barriers;”
Paschall teaches, (Page 30, Column 34, Lines 57-67 & Page 31, Column 35, Lines 1-3) “The data storage 1235 may include various data stores for maintaining data related to systems, operations, or processes described herein, such as facility or environment data including characteristics of the environment, AMR data, identifier or code data, sensor data, safety zone data, separation distance data, detected object data, navigation data, drive mechanism data, path or destination data, movement characteristics data including position, speed, acceleration, weight, load, planned path, destination, or other movement characteristics, lift mechanism data, other sensor data, material handling equipment or apparatus, upstream systems, stations, or processes, downstream systems, stations, or processes, etc.”
“predicting a maximum value of displacement between a self-recognition position and an actual position; and estimating the self-recognition position,”
Paschall does not explicitly teach the preceding limitations related to predicting a maximum value of displacement between a self-recognition position and an actual position.
Park does teach the preceding limitations.
Park teaches, (Abstract, Lines 1-2) “an unmanned aerial vehicle formation control system,” in reference to description of scenario present in the prior art wherein, (Paragraph [0009], Lines 1-5) “in a formation flight (A1) of agricultural unmanned aerial vehicles, each agricultural unmanned aerial vehicle flies in formation based on the provided location data, so that a control overlap zone 10 or a no-control zone 20 occurs,” the reference of which is relevant to the applicant’s disclosure due to its teachings of measuring the maximum value of displacement between a self-recognition position and an actual position in the context of a vehicle platoon.
Park teaches a, (Abstract, Lines 4-15) “system including a data processing unit that receives the location data and distance data of the unmanned aerial vehicles and provides the received location data and distance data to other unmanned aerial vehicles belonging to a formation of the unmanned aerial vehicles; a formation alignment unit that selectively uses the location data and the distance data to align the formation of the unmanned aerial vehicles; and a formation error determination unit that calculates an overall formation error value due to formation alignment mismatch based on the location data of the unmanned aerial vehicle, and compares the formation error value with a preset allowable threshold value to determine whether a formation error of the unmanned aerial vehicle has occurred.”
“requesting communication in a case where it is determined that there is a possibility that the mobile body is outside the virtual barrier in consideration of the maximum value of the displacement,”
Park teaches, (Paragraph [0066]) “the formation control system 200 may compare the overall formation error value with a preset allowable threshold value to determine whether a formation error has occurred. When it is determined that a formation error has occurred, the formation control system 200 may realign the leader unmanned aerial vehicle 110 and the follower unmanned aerial vehicle 120 based on location data. That is, when it is determined that a formation error has occurred, the formation control system 200 may switch from controlling a formation based on distance data to controlling the formation based on location data.” Examiner is interpreting the switching of controlling a formation based on distance data to controlling the formation based on location data as part of a realignment operating as an example of the system requesting communication under broadest reasonable interpretation. The interpretation is derived from Applicant’s specification, which reads, (Paragraph [0011], Lines 7-8) “transmitting and receiving, according to a request, the paths and the virtual barriers, or further positions of the mobile bodies,” the preceding teachings being interpreted as an example of transmitting and receiving further positions of the mobile bodies.
“and updating the self-recognition position.”
Park teaches, (Paragraph [0089-0090]) “when a formation error has occurred, the formation alignment unit 230 may switch the unmanned aerial vehicle 100, which has been controlled based on distance data, to be controlled based on location data,” and that, “Additionally, the formation alignment unit 230 may realign the unmanned aerial vehicle 100 based on location data, and then switch back to controlling the unmanned aerial vehicle 100 based on distance data,” wherein, (Paragraph [0055], Lines 4-6) “the leader unmanned aerial vehicle 110 may measure distance data from the follower unmanned aerial vehicle 120 adjacent thereto using the distance measurement sensor.”
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to combine the autonomous mobile robot platooning system which is capable of maintaining a separation difference between robots within a desired region as taught by Paschall, with the explicit teachings of predicting a maximum value of displacement between a self-recognition position and an actual position in context of a group of leader/follower robots as taught by Park, in order to yield predictable results.
Combining the references would yield the benefits of minimizing accumulated error during the travel of a vehicle platoon by comparing the desired vs actual locations of the vehicle, the error of which could introduce collision or entrance of the vehicles into unwanted areas. As Park describes, (Paragraph [0031]) “according to an embodiment of the present disclosure, a formation control system may perform formation alignment based on location data of unmanned aerial vehicles, and then control a formation form to be maintained constant based on distance data of the unmanned aerial vehicles, thereby minimizing formation error accumulation that may occur in location data-based formation control as in the related art.”
Claim 5 Discloses: (Original)
“The control method according to claim 4, wherein the displacement is reset to 0 after a timing at which the self-recognition position is updated and a timing at which the position of the follower mobile body is calculated.”
Paschall does not explicitly teach resetting the displacement to 0 after a timing at which the self-recognition position is updated and a timing at which the position of the follower mobile body is calculated.
Park does teach the preceding limitations.
Park teaches, (Paragraph [0058], Lines 1-2) “the follower unmanned aerial vehicle 120 may measure location data using the location measurement sensor,” and that (Paragraph [0079]) “the formation error determination unit 220 may calculate a formation error value using the location data of the unmanned aerial vehicle 100 received in real time and ideal location data of the unmanned aerial vehicle 100 at the corresponding point in time. For example, the formation error determination unit 220 may calculate a difference between the real-time measured location data of the leader unmanned aerial vehicle and the follower unmanned aerial vehicle included in the unmanned aerial vehicle 100 and the ideal location data of each of the leader unmanned aerial vehicle and the follower unmanned aerial vehicle at that point in time as a formation error value. At this time, the formation error value may be derived for each of the leader unmanned aerial vehicle and the follower unmanned aerial vehicle.”
Park additionally teaches, (Paragraph [0088]) “when the formation error determination unit 230 determines that a formation error has occurred, the formation alignment unit 230 may realign the formation of the unmanned aerial vehicle 100 based on the location data of the unmanned aerial vehicle 100,” and that, (Paragraph [0090]) “the formation alignment unit 230 may realign the unmanned aerial vehicle 100 based on location data, and then switch back to controlling the unmanned aerial vehicle 100 based on distance data.” Note: once the formulation error surpassed a threshold as in cited Paragraph [0088], realignment may occur. During the realignment, the system of Park switches the manner in which it measures location to “distance data” to start a new and remove the measurement error.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to combine the autonomous mobile robot platooning system which is capable of maintaining a separation difference between robots within a desired region as taught by Paschall, with the explicit teachings of predicting a maximum value of displacement between a self-recognition position and an actual position in context of a group of leader/follower robots and subsequent time based alignment iteration which resets the displacement to zero as taught by Park, in order to yield predictable results.
Combining the references would yield the benefits of minimizing accumulated error over time during the travel of a vehicle platoon by comparing the desired vs actual locations of the vehicle, the error of which could introduce collision or entrance of the vehicles into unwanted areas. As Park describes, (Paragraph [0031]) “according to an embodiment of the present disclosure, a formation control system may perform formation alignment based on location data of unmanned aerial vehicles, and then control a formation form to be maintained constant based on distance data of the unmanned aerial vehicles, thereby minimizing formation error accumulation that may occur in location data-based formation control as in the related art.”
Claim 6 Discloses: (Original)
“The control method according to claim 4, wherein the self-recognition position is updated when the leader mobile body receives a self-position.”
Paschall does not explicitly teach updating the self-recognition position when the leader mobile body receives a self-position.
Park does teach the preceding limitations.
Park teaches, (Paragraph [0055]) “the leader unmanned aerial vehicle 110 may perform a formation flight based on location data acquired by the location measurement sensor. Furthermore, the leader unmanned aerial vehicle 110 may measure distance data from the follower unmanned aerial vehicle 120 adjacent thereto using the distance measurement sensor. The leader unmanned aerial vehicle 110 may share the measured location data and distance data with the follower unmanned aerial vehicle 110 through the formation control system 200,” and that (Paragraph [0079]) “the formation error determination unit 220 may calculate a formation error value using the location data of the unmanned aerial vehicle 100 received in real time and ideal location data of the unmanned aerial vehicle 100 at the corresponding point in time. For example, the formation error determination unit 220 may calculate a difference between the real-time measured location data of the leader unmanned aerial vehicle and the follower unmanned aerial vehicle included in the unmanned aerial vehicle 100 and the ideal location data of each of the leader unmanned aerial vehicle and the follower unmanned aerial vehicle at that point in time as a formation error value. At this time, the formation error value may be derived for each of the leader unmanned aerial vehicle and the follower unmanned aerial vehicle.”
Park additionally teaches, (Paragraph [0088]) “when the formation error determination unit 230 determines that a formation error has occurred, the formation alignment unit 230 may realign the formation of the unmanned aerial vehicle 100 based on the location data of the unmanned aerial vehicle 100,” and that, (Paragraph [0090]) “the formation alignment unit 230 may realign the unmanned aerial vehicle 100 based on location data, and then switch back to controlling the unmanned aerial vehicle 100 based on distance data.”
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to combine the autonomous mobile robot platooning system which is capable of maintaining a separation difference between robots within a desired region as taught by Paschall, with the explicit teachings of predicting a maximum value of displacement between a self-recognition position and an actual position in context of a group of leader/follower robots and subsequent time based alignment iteration as taught by Park, in order to yield predictable results.
Combining the references would yield the benefits of minimizing accumulated error over time during the travel of a vehicle platoon by comparing the desired vs actual locations of the vehicle, the error of which could introduce collision or entrance of the vehicles into unwanted areas. As Park describes, (Paragraph [0031]) “according to an embodiment of the present disclosure, a formation control system may perform formation alignment based on location data of unmanned aerial vehicles, and then control a formation form to be maintained constant based on distance data of the unmanned aerial vehicles, thereby minimizing formation error accumulation that may occur in location data-based formation control as in the related art.”
Claim 7 Discloses: (Currently Amended)
“A non-transitory computer-readable recording medium recording a program including an instruction for causing a computer to:”
Paschall teaches, (Abstract, Lines 1-2) “Autonomous mobile robots (AMRs) having adaptive safety systems [which] may operate individually or as part of a convoy,” wherein, (Page 28, Column 29, Lines 58-61) “the AMR control system 1100 includes one or more processors 1102, coupled to a non-transitory computer readable storage medium 1120 via an input/output (I/O) interface 1110,” and that, (Page 28, Column 30, Lines 13-15) “The non-transitory computer readable storage medium 1120 may be configured to store executable instructions, applications, drivers, and/or data, such as AMR data.”
“set a path of each mobile body in a formation controlled in such a way that a leader mobile body makes a follower mobile body follow;”
Paschall teaches, (Page 19, Column 11, Lines 11-13) “During convoy operations, a first, or leader, AMR 305 may modify one or more movement characteristics to operate as a leader of the convo e.g., modify speed, direction, or path,” and further teaches, (Page 14, Column 2, Lines 37-41) “Using the adaptive safety systems as further described herein to enable convoy operations, two or more autonomous mobile robots, e.g., including a leader autonomous mobile robot and one or more follower autonomous mobile robots.”
“set virtual barriers indicating safe regions of the mobile bodies;”
Paschall teaches, (Abstract, Lines 3-4) “an AMR may determine a safety zone,” and, (Page 14, Column 2, Lines 64-67 & Page 15, Column 3, Lines 1-3) “In addition, the first and second AMRs may navigate within structured areas or fields, e.g., areas having identifiers, codes, or other markings associated with various locations that aid navigation and location determination, or within unstructured areas or fields, e.g., areas without identifiers, codes, or other markings associated with various locations.”
“measure relative coordinates with the another mobile body and calculate a position of the follower mobile body recognized by the leader mobile body;”
Paschall teaches, (Page 22, Column 18, Lines 34-44) “the leader AMR may modify one or more movement characteristics in order to facilitate formation of the convoy that will follow the leader AMR. For example, the one or more movement characteristics may include modifying speed, stopping, accelerating, decelerating, changing direction, turning, adjusting a path, rerouting, maintaining defined separation distances, and/or other modifications to movement characteristics. In some example embodiments, a leader AMR may slow or stop in order to allow one or more follower AMRs to catch up to and follow the leader AMR,” and that, (Page 18, Column 9, Lines 14-16) “the safety system controller 233 may process the data associated with detected objects, which may include transposing the data to a desired coordinate system.”
Paschall additionally teaches, (Page 14, Column 2, Lines 44-48) “The one or more follower autonomous mobile robots may substantially continuously or intermittently detect the leader, or a preceding, autonomous mobile robot in order to maintain the convoy operations.”
“transmit and receive, according to a request,”
Paschall teaches, (Page 22, Column 18, Lines 10-11) “FIG. 7 is a flow diagram illustrating an example convoy formation process 700,” wherein, (Page 22, Column 18, Lines 21-25) “the control system may send or transmit instructions or commands to the AMRs to form the convoy with the determined movement characteristics, as well as data or information, e.g., identifier or codes, associated one or more other AMRs that are to form the convoy,” and that, (Page 23, Column 19, Lines 8-10) “In addition, each follower AMR may receive data or information associated with the leader or preceding AMR that the follower AMR is to detect, identify, and follow.”
“the paths and the virtual barriers,”
Paschall teaches, (Page 23, Columns 19 Line 66-67 & Page 23 Column 20, Lines 1-8) “the detected identifier does match the expected identifier that the follower AMR is to identify and follow, then the process 700 may continue with muting, by the controller of the follower AMR, a forward portion of a safety zone of the follower AMR, as at 712. For example, a portion of the safety zone of the follower AMR may be selectively muted to permit or allow a portion of the leader or preceding AMR, and its associated identifier, within the portion of the safety zone, e.g., toward a forward movement direction of the follower AMR.”
“or further positions of the mobile bodies;”
Paschall teaches, (Page 23, Column 20, lines 25-32) “The process 700 may proceed with adjusting, by a controller of a leader AMR, movement characteristics for convoy operation, as at 714. For example, based on the received instructions to form a convoy with one or more other AMRs and based on a determination that the AMRs have completed formation of the convoy, the leader AMR may modify one or more movement characteristics in order to lead the convoy.”
“store the set paths; store the set virtual barriers;”
Paschall teaches, (Page 30, Column 34, Lines 57-67 & Page 31, Column 35, Lines 1-3) “The data storage 1235 may include various data stores for maintaining data related to systems, operations, or processes described herein, such as facility or environment data including characteristics of the environment, AMR data, identifier or code data, sensor data, safety zone data, separation distance data, detected object data, navigation data, drive mechanism data, path or destination data, movement characteristics data including position, speed, acceleration, weight, load, planned path, destination, or other movement characteristics, lift mechanism data, other sensor data, material handling equipment or apparatus, upstream systems, stations, or processes, downstream systems, stations, or processes, etc.”
“predict a maximum value of displacement between a self-recognition position and an actual position; and estimate the self-recognition position,”
Paschall does not explicitly teach the preceding limitations related to predicting a maximum value of displacement between a self-recognition position and an actual position.
Park does teach the preceding limitations.
Park teaches, (Abstract, Lines 1-2) “an unmanned aerial vehicle formation control system,” in reference to description of scenario present in the prior art wherein, (Paragraph [0009], Lines 1-5) “in a formation flight (A1) of agricultural unmanned aerial vehicles, each agricultural unmanned aerial vehicle flies in formation based on the provided location data, so that a control overlap zone 10 or a no-control zone 20 occurs,” the reference of which is relevant to the applicant’s disclosure due to its teachings of measuring the maximum value of displacement between a self-recognition position and an actual position in the context of a vehicle platoon.
Park teaches a, (Abstract, Lines 4-15) “system including a data processing unit that receives the location data and distance data of the unmanned aerial vehicles and provides the received location data and distance data to other unmanned aerial vehicles belonging to a formation of the unmanned aerial vehicles; a formation alignment unit that selectively uses the location data and the distance data to align the formation of the unmanned aerial vehicles; and a formation error determination unit that calculates an overall formation error value due to formation alignment mismatch based on the location data of the unmanned aerial vehicle, and compares the formation error value with a preset allowable threshold value to determine whether a formation error of the unmanned aerial vehicle has occurred.”
“request communication in a case where it is determined that there is a possibility that the mobile body is outside the virtual barrier in consideration of the maximum value of the displacement,”
Park teaches, (Paragraph [0066]) “the formation control system 200 may compare the overall formation error value with a preset allowable threshold value to determine whether a formation error has occurred. When it is determined that a formation error has occurred, the formation control system 200 may realign the leader unmanned aerial vehicle 110 and the follower unmanned aerial vehicle 120 based on location data. That is, when it is determined that a formation error has occurred, the formation control system 200 may switch from controlling a formation based on distance data to controlling the formation based on location data.” Examiner is interpreting the switching of controlling a formation based on distance data to controlling the formation based on location data as part of a realignment operating as an example of the system requesting communication under broadest reasonable interpretation. The interpretation is derived from Applicant’s specification, which reads, (Paragraph [0011], Lines 7-8) “transmitting and receiving, according to a request, the paths and the virtual barriers, or further positions of the mobile bodies,” the preceding teachings being interpreted as an example of transmitting and receiving further positions of the mobile bodies.
“and update the self- recognition position.”
Park teaches, (Paragraph [0089-0090]) “when a formation error has occurred, the formation alignment unit 230 may switch the unmanned aerial vehicle 100, which has been controlled based on distance data, to be controlled based on location data,” and that, “Additionally, the formation alignment unit 230 may realign the unmanned aerial vehicle 100 based on location data, and then switch back to controlling the unmanned aerial vehicle 100 based on distance data,” wherein, (Paragraph [0055], Lines 4-6) “the leader unmanned aerial vehicle 110 may measure distance data from the follower unmanned aerial vehicle 120 adjacent thereto using the distance measurement sensor.”
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to combine the autonomous mobile robot platooning system which is capable of maintaining a separation difference between robots within a desired region as taught by Paschall, with the explicit teachings of predicting a maximum value of displacement between a self-recognition position and an actual position in context of a group of leader/follower robots as taught by Park, in order to yield predictable results.
Combining the references would yield the benefits of minimizing accumulated error during the travel of a vehicle platoon by comparing the desired vs actual locations of the vehicle, the error of which could introduce collision or entrance of the vehicles into unwanted areas. As Park describes, (Paragraph [0031]) “according to an embodiment of the present disclosure, a formation control system may perform formation alignment based on location data of unmanned aerial vehicles, and then control a formation form to be maintained constant based on distance data of the unmanned aerial vehicles, thereby minimizing formation error accumulation that may occur in location data-based formation control as in the related art.”
Claim 8 Discloses: (Currently Amended)
“The non-transitory computer-readable recording medium according to claim 7, for further causing the computer to reset the displacement to 0 after a timing at which the self-recognition position is updated and a timing at which the position of the follower mobile body is calculated.”
Paschall does not explicitly teach resetting the displacement to 0 after a timing at which the self-recognition position is updated and a timing at which the position of the follower mobile body is calculated.
Park does teach the preceding limitations.
Park teaches, (Paragraph [0058], Lines 1-2) “the follower unmanned aerial vehicle 120 may measure location data using the location measurement sensor,” and that (Paragraph [0079]) “the formation error determination unit 220 may calculate a formation error value using the location data of the unmanned aerial vehicle 100 received in real time and ideal location data of the unmanned aerial vehicle 100 at the corresponding point in time. For example, the formation error determination unit 220 may calculate a difference between the real-time measured location data of the leader unmanned aerial vehicle and the follower unmanned aerial vehicle included in the unmanned aerial vehicle 100 and the ideal location data of each of the leader unmanned aerial vehicle and the follower unmanned aerial vehicle at that point in time as a formation error value. At this time, the formation error value may be derived for each of the leader unmanned aerial vehicle and the follower unmanned aerial vehicle.”
Park additionally teaches, (Paragraph [0088]) “when the formation error determination unit 230 determines that a formation error has occurred, the formation alignment unit 230 may realign the formation of the unmanned aerial vehicle 100 based on the location data of the unmanned aerial vehicle 100,” and that, (Paragraph [0090]) “the formation alignment unit 230 may realign the unmanned aerial vehicle 100 based on location data, and then switch back to controlling the unmanned aerial vehicle 100 based on distance data.”
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to combine the autonomous mobile robot platooning system which is capable of maintaining a separation difference between robots within a desired region as taught by Paschall, with the explicit teachings of predicting a maximum value of displacement between a self-recognition position and an actual position in context of a group of leader/follower robots and subsequent time based alignment iteration which resets the displacement to zero as taught by Park, in order to yield predictable results.
Combining the references would yield the benefits of minimizing accumulated error over time during the travel of a vehicle platoon by comparing the desired vs actual locations of the vehicle, the error of which could introduce collision or entrance of the vehicles into unwanted areas. As Park describes, (Paragraph [0031]) “according to an embodiment of the present disclosure, a formation control system may perform formation alignment based on location data of unmanned aerial vehicles, and then control a formation form to be maintained constant based on distance data of the unmanned aerial vehicles, thereby minimizing formation error accumulation that may occur in location data-based formation control as in the related art.”
Claim 9 Discloses: (Currently Amended)
“The non-transitory computer-readable recording medium according to claim 7, for further causing the computer to update the self-recognition position when the leader mobile body receives a self- position.”
Paschall does not explicitly teach updating the self-recognition position when the leader mobile body receives a self-position.
Park does teach the preceding limitations.
Park teaches, (Paragraph [0055]) “the leader unmanned aerial vehicle 110 may perform a formation flight based on location data acquired by the location measurement sensor. Furthermore, the leader unmanned aerial vehicle 110 may measure distance data from the follower unmanned aerial vehicle 120 adjacent thereto using the distance measurement sensor. The leader unmanned aerial vehicle 110 may share the measured location data and distance data with the follower unmanned aerial vehicle 110 through the formation control system 200,” and that (Paragraph [0079]) “the formation error determination unit 220 may calculate a formation error value using the location data of the unmanned aerial vehicle 100 received in real time and ideal location data of the unmanned aerial vehicle 100 at the corresponding point in time. For example, the formation error determination unit 220 may calculate a difference between the real-time measured location data of the leader unmanned aerial vehicle and the follower unmanned aerial vehicle included in the unmanned aerial vehicle 100 and the ideal location data of each of the leader unmanned aerial vehicle and the follower unmanned aerial vehicle at that point in time as a formation error value. At this time, the formation error value may be derived for each of the leader unmanned aerial vehicle and the follower unmanned aerial vehicle.”
Park additionally teaches, (Paragraph [0088]) “when the formation error determination unit 230 determines that a formation error has occurred, the formation alignment unit 230 may realign the formation of the unmanned aerial vehicle 100 based on the location data of the unmanned aerial vehicle 100,” and that, (Paragraph [0090]) “the formation alignment unit 230 may realign the unmanned aerial vehicle 100 based on location data, and then switch back to controlling the unmanned aerial vehicle 100 based on distance data.”
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to combine the autonomous mobile robot platooning system which is capable of maintaining a separation difference between robots within a desired region as taught by Paschall, with the explicit teachings of predicting a maximum value of displacement between a self-recognition position and an actual position in context of a group of leader/follower robots and subsequent time based alignment iteration as taught by Park, in order to yield predictable results.
Combining the references would yield the benefits of minimizing accumulated error over time during the travel of a vehicle platoon by comparing the desired vs actual locations of the vehicle, the error of which could introduce collision or entrance of the vehicles into unwanted areas. As Park describes, (Paragraph [0031]) “according to an embodiment of the present disclosure, a formation control system may perform formation alignment based on location data of unmanned aerial vehicles, and then control a formation form to be maintained constant based on distance data of the unmanned aerial vehicles, thereby minimizing formation error accumulation that may occur in location data-based formation control as in the related art.”
RELEVANT, BUT NOT CITED PRIOR ART
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Suzuki et al., (US 20200333789 A1) discloses, (Paragraph [0162], Lines 27-40) “when the distance between an arbitrary point included in the area representing the route and the position coordinates of the mobile object 11 is equal to or smaller than a predetermined value (for example, 1 m), it is determined that the mobile object 11 is on the route. When the mobile object 11 is on the route, the position/orientation information is sent to the movement control unit 1116 as the position/orientation information of the mobile object 11. However, when the position/orientation information is not on the route, that is, when the position/orientation information is apart from the route by a predetermined distance or more (for example, 1 m or more), it is determined that the mobile object 11 deviates from the correct route along which the mobile object 11 is supposed to travel.”
Machida (US 2024/0134396 A1) discloses, (Paragraph [0034]) “The constraint condition calculation unit 12 calculates constraint condition candidates using the position information and the constraint-related information transmitted and received via the communication unit 11, and identifies the constraint condition used for controlling the position of the first robot using the time information. The constraint condition calculation unit 12 sets a constraint condition in such a way that the distance between the robot (for example, a second robot) operating in cooperation and the first robot is equal to or less than the distance R. The value of the distance R is set in advance based on, for example, a communicable distance between a plurality of robots and a distance between robots suitable for the use of the robot.”
Conclusion
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/ALEXANDER V GENTILE/Examiner, Art Unit 3664
/KITO R ROBINSON/Supervisory Patent Examiner, Art Unit 3664
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