DETAILED ACTION
Response to Amendment
This office action regarding application number 18/290,311, filed November 13, 2023, in in response to applicants arguments and amendments filed August 4, 2026. Claims 1, 6, and 8 have been amended. Claims 4 and 7 have been cancelled. Claims 1-3, 5-6 and 8 are currently pending and are addressed below.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 8/4/2026 has been entered.
Response to Arguments
The applicants arguments and amendments to the application have overcome some of the objections and rejections previously set forth in the Final action mailed June 16, 2026. Claims 4 and 7 have been cancelled, therefore all associated objections and rejections are withdrawn. Applicants amendments to claim 8 have removed the language being interpreted under 35 USC 112(f), therefore most of the interpretations are withdrawn.
However, Applicants amendments to claim 1 have NOT been deemed sufficient to overcome the previous 35 USC 103 rejections through the inclusion of “monitor a time correlation of data related to the operation state transmitted from the second autonomous traveling machine and set the verification point when data deviating from the time correlation is observed” these limitations are found to be identical to the cancelled claim 4 and taught by the combination of the Ohno and Ghosh references, therefore the rejections are maintained with changes to reflect amendments. Additionally the applicants arguments have been fully considered but are not fully persuasive for the reasons seen below.
On pages 9-10 the applicant argues “However, the ToF measurements in Ghosh merely relate to a comparison of a radio arrival time for measuring distance, which has a different purpose and structure from the presently claimed invention as set forth in claim 1. Claim 1 relates to data deviating from a time correlation and when data deviating from the time correlation is observed a verification point is set. That is, claim 1 relates to deviation monitoring of a communication period, for example, for determining an inconsistency which may be caused by a suspected cyber attack. That is, Ghosh does not disclose "monitor a time correlation of data related to the operation state transmitted from the second autonomous traveling machine and set the verification point when data deviating from the time correlation is observed," as set forth in claim 1.”, the examiner respectfully disagrees.
MPEP 2142-2144 discusses the requirements for a case of obviousness using 35 USC 103 and provides examples of such cases. MPEP 2111 discusses Broadest Reasonable Interpretation and the interpretation of claims.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
As discussed in the rejections below the rejection is based on the combination of the Ohno and Ghosh references. Ohno teaches monitor a time correlation of data related to the operation state transmitted from the second autonomous traveling machine (Paragraph [0153], “The AGV 10 may temporarily stop at the position of each marker, perform localization, and give a notification to the terminal device 20; in this case the data of each marker may include data of the acceleration time required until reaching the traveling speed and/or data of the deceleration time required until the vehicle traveling at that traveling speed stops at the position of the next marker” here the system is correlating the series of points with the expected time to reach the next the next point).
Ohno does not explicitly teach set the verification point when data deviating from the time correlation is observed, however this limitation is taught by Ghosh (Paragraph [0215], “The procedures described above relative to the one or more processors of the first vehicle and the one or more processors of the second vehicle may be performed multiple times. The number of times that these procedures must be performed may be determined by a degree of synchronization between the one or more processors of the first vehicle and the one or more processors of the second vehicle. Unless a high degree of synchronization is present, multiple ToF measurements may be necessary. In cases of less than ideal synchronization, it may be known to perform three or more ToF measurements.”) (Paragraph [0244], “The signal quality as described herein may be any signal quality including, but not limited to any of a signal strength, a time stamp, a ToF, or any combination thereof.”) (Paragraph [0096], “a ToF operation is performed between the UAV 502 and the base station 504. An expected ToF may be determined based on the calculated distance between the reported position of the UAV 502 and the known position of the base station at 504 using a distance derived by equation (1) and the speed of light, such as 299,792,458 m/s. Using a ToF transmission, a measured ToF between the UAV 502 and the base station 504 may be determined. The expected ToF and measured ToF may be compared. If the expected ToF and measured ToF are within a reasonable tolerance,” here the flight path is correlated with a time of flight measurement which can be used to verify the position of the machine based on the synchronization of the ToF measurements) (Paragraph [0423], “wherein the one or more processors are further configured to determine a discrepancy between the determined first position and first orientation, and the received position of the orientation of the remote signal source relative to at least one of the at least three antennas; and if the discrepancy is greater than a predetermined threshold, redetermine the first position and first orientation.”). Here Ghosh is teaching setting a verification point based on the measured and expected time measurements being within a reasonable tolerance.
Therefore the combination of Ohno and Ghosh teaches monitor a time correlation of data related to the operation state transmitted from the second autonomous traveling machine and set the verification point when data deviating from the time correlation is observed, therefore the rejections under 35 USC 103 are maintained.
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., “a situation, for example in which the safety management system itself is hacked and control is taken away”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
On pages 11-13 the applicant argues “The limitations of previously presented claim 7, now in claim 6, do not relate to generating reliability data indicating a degree of coincidence of the local map data with map data M in Ohno. Therefore, Ohno does not disclose "wherein each of the processors of the first and second autonomous traveling machines is configured to determine whether there is a contradiction or inconsistency between the first and second safety-ensuring operation instructions, and give a notification of an abnormality of the safety management system when determining that there is a contradiction or inconsistency," as set forth in claim 6. Further, resort to Ghosh, which is discussed above, does not cure the deficiencies in Ohno. For at least the reasons presented herein, the cited combination of documents does not teach or suggest all of the elements of claim 1 and 6. Accordingly, Applicant submits that the cited combination of documents does not render independent claims 1 or 6 unpatentable, and respectfully requests that the Office withdraw the § 103 rejection of claims 1 and 6.”, the examiner respectfully disagrees.
MPEP 2142-2144 discusses the requirements for a case of obviousness using 35 USC 103 and provides examples of such cases. MPEP 2111 discusses Broadest Reasonable Interpretation and the interpretation of claims.
As discussed in the rejections below Ohno teaches wherein each of the processors of the first and second autonomous traveling machines is configured to determine whether there is a contradiction or inconsistency between the first and second safety-ensuring operation instructions (Paragraph [0157], "The localization device 14e identifies the AGV's position (x, y, θ) on the map data M by matching the local map data (or sensor data) generated from the scanning results of the laser range finder 15 against wider-range map data M. The localization device 14e generates “reliability” data indicating the degree of coincidence of the local map data with the map data M,” here the system is using the verification position information according to the determined path in order to compare the sensed position and determine an inconsistency in control of the vehicle)
and give a notification of an abnormality of the safety management system when determining that there is a contradiction or inconsistency (Paragraph [0157], “The terminal device 20 or the navigation management device 50 may receive the respective data of the AGV's position (x, y, θ) and the reliability and may display the data on a display that is built therein or connected thereto.”).
Regarding claim 6 the limitations of determining a contradiction or inconsistency is taught by Ohno in the form of the reliability determination. The examiner would like to note that these limitations are also taught by the Ghosh reference which transmits a flight path/safety ensuring instruction to the vehicles and determines inconsistency in the vehicle by comparing the detected position of the vehicle to the reported position of the vehicle based on the transmitted flight paths.
Therefore the combination of Ohno, Ghosh, and Guo teaches wherein each of the processors of the first and second autonomous traveling machines is configured to determine whether there is a contradiction or inconsistency between the first and second safety-ensuring operation instructions, and give a notification of an abnormality of the safety management system when determining that there is a contradiction or inconsistency, therefore the rejections under 35 USC 103 are maintained.
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 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.
Claim 1-3 5-6 and 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ohno (US-20190294181) in view of Ghosh (US-20200043348) and further in view of Guo (US 20220026566).
Regarding claim 1, Ohno teaches a safety management system for giving an instruction of a safety ensuring operation to each of a first autonomous traveling machine, having a processor and a sensor, and a second autonomous traveling machine having a processor and a sensor (Paragraph [0050], "The vehicle management system 100 includes: a plurality of vehicles 10 capable of traveling autonomously; a navigation management device (which hereafter may simply be referred to as the “management device”) 50 configured to manage navigation of the plurality of vehicles 10")
the first autonomous traveling machine being configured to (Paragraph [0051], "The vehicle management system 100 may include three or more vehicles 10. In this embodiment, the vehicle 10 is an automated guided vehicle (AGV). In the following description, the vehicle 10 may also be referred to as the “AGV 10”.”)
recognize a surrounding situation to transmit first surrounding situation data (Paragraph [0055], "Each vehicle 10 has a function of detecting an obstacle on the traveling path and a function of notifying presence of the detected obstacle to the outside.")
transmit an own operation state (EXAMINERS NOTE: Here the examiner refers to the specification to interpret “operation state”, paragraph [0018] recites “Hereinafter, the own position, traveling direction, speed, and posture will be collectively referred to as an operation state,” therefore “operation state” is interpreted as traveling information for the vehicle) (Paragraph [0062], "As a result, if the vehicle 10 has found a traveling path to the position of the next target marker, the vehicle 10 may transmit the obstacle avoidance path (i.e., the altered traveling path) to the management device 50,” here the system is transmitting an avoidance path which includes at least position, direction, speed and therefore is transmitting an operation state)
and autonomously travel on a given first traveling route based on the first surrounding situation data (Paragraph [0055], "The controller 14a causes the vehicle 10 to travel along the traveling path determined by the processing circuit 51 by controlling a driving device which is not shown.")
the second autonomous traveling machine being configured to (Paragraph [0051], "The vehicle management system 100 may include three or more vehicles 10. In this embodiment, the vehicle 10 is an automated guided vehicle (AGV). In the following description, the vehicle 10 may also be referred to as the “AGV 10”.”)
recognize a surrounding situation to transmit second surrounding situation data (Paragraph [0055], "Each vehicle 10 has a function of detecting an obstacle on the traveling path and a function of notifying presence of the detected obstacle to the outside.")
transmit an own operation state (EXAMINERS NOTE: Here the examiner refers to the specification to interpret “operation state”, paragraph [0018] recites “Hereinafter, the own position, traveling direction, speed, and posture will be collectively referred to as an operation state,” therefore “operation state” is interpreted as traveling information for the vehicle) (Paragraph [0062], "As a result, if the vehicle 10 has found a traveling path to the position of the next target marker, the vehicle 10 may transmit the obstacle avoidance path (i.e., the altered traveling path) to the management device 50,” here the system is transmitting an avoidance path which includes at least position, direction, speed and therefore is transmitting an operation state)
and autonomously travel on a given second traveling route based on the second surrounding situation data (Paragraph [0055], "The controller 14a causes the vehicle 10 to travel along the traveling path determined by the processing circuit 51 by controlling a driving device which is not shown.")
the safety management system comprising: a processor and a memory coupled to the processor storing instructions that when executed by the processor, configures the processor to (Paragraph [0146], “The travel control device 14 includes an MCU 14a, a memory 14b, a storage device 14c, a communication circuit 14d, and a localization device 14e. The MCU 14a, the memory 14b, the storage device 14c, the communication circuit 14d, and the localization device 14e are connected via a communication bus 14f, so as to be capable of exchanging data with one another.”)
set a verification point (Paragraph [0083], "The data of all markers may be transmitted to each vehicle 10 before the start of travel. As described above, as another example, the management device 50 may transmit the data of a next marker to each vehicle 10. In the latter application, the management device 50 receives the information of the present position of each vehicle 10 periodically, for example, every 100 msec, from each vehicle 10, thereby grasping the present position of each vehicle 10. Upon determining that there is a vehicle 10 that has reached the position of the designated marker, the management device 50 transmits the data of the next marker to that vehicle 10," here the system can set a series of points for each vehicle) (Paragraph [0153], "The AGV 10 may temporarily stop at the position of each marker, perform localization, and give a notification to the terminal device 20," the system can further perform a position verification at each point)
and extract an operation state of the second autonomous traveling machine at the verification point from the first surrounding situation data (Paragraph [0143], "The travel control device 14 can estimate the current position of the device itself by comparing the measurement results of the laser range finder 15 with the map data stored in itself. The map data stored in the device may have been generated by another AGV 10.”) (Paragraph [0153], "The AGV 10 may temporarily stop at the position of each marker, perform localization, and give a notification to the terminal device 20," the system can further perform a position verification at each point)
to verify a soundness of control on the second autonomous traveling machine (Paragraph [0157], "The localization device 14e identifies the AGV's position (x, y, θ) on the map data M by matching the local map data (or sensor data) generated from the scanning results of the laser range finder 15 against wider-range map data M. The localization device 14e generates “reliability” data indicating the degree of coincidence of the local map data with the map data M,” here the system is using the verification position information in order to compare the sensed position and determine a reliability/soundness of control of the vehicle)
and monitor a time correlation of data related to the operation state transmitted from the second autonomous traveling machine (Paragraph [0153], “The AGV 10 may temporarily stop at the position of each marker, perform localization, and give a notification to the terminal device 20; in this case the data of each marker may include data of the acceleration time required until reaching the traveling speed and/or data of the deceleration time required until the vehicle traveling at that traveling speed stops at the position of the next marker” here the system is correlating the series of points with the expected time to reach the next the next point).
However Ohno does not explicitly teach the verification point at which the second autonomous traveling machine is recognizable by the first autonomous traveling machine in the second traveling route and a verification unit configured to compare an operation state transmitted from the second autonomous traveling machine at the verification point with the operation state extracted by the extraction unit to verify soundness of control on the second autonomous traveling machine and set the verification point when data deviating from the time correlation is observed.
Ghosh teaches methods and devices for positioning autonomous agents by verifying a reported agent location including
the verification point at which the second autonomous traveling machine is recognizable by the first autonomous traveling machine in the second traveling route (Paragraph [0086], "For example, UAV position may be estimated or verified based on blind signal processing relying on signal quality, such as angle of arrival. A plurality of base stations, each having multiple antennas, may be available to receive or transmit signals from one or more UAVs. Similarly, a plurality of UAVs may be available to receive signals of one or more other UAVs. When there are multiple antennas at the different base stations (or at the UAVs), these multiple antennas can be used to estimate the angle of arrival of the received signal from the UAV, which is closely related to the angular elevation of the UAV from each of these base stations. These values can then be used to estimate the position using conventional localization techniques that can estimate position from angles of arrival," here the system is using a first machine/UAV in order to determine/recognize the position of a second machine/UAV)
and compare an operation state transmitted from the second autonomous traveling machine at the verification point with the extracted operation state of the second autonomous traveling machine (Paragraph [0091], “Having detected in approximate position of the UAV (202 or 302), the detected position of the UAV (202 or 302) may be compared with the reported position from the UAV (202 or 302)”)
to verify soundness of control on the second autonomous traveling machine (Paragraph [0091], “If the detected position and the reported position correspond within an acceptable tolerance, a level of verification of the reported UAV is established. If the detected position and the reported position do not correspond within an acceptable level of tolerance, the reported UAV position may be inaccurate. In this situation, further procedures may be instituted, as desired for the implementation, to address the unverified or disputed reported UAV position”)
based on whether there is a difference between the extracted operation state of the second autonomous traveling machine and the transmitted operation state transmitted from the second autonomous traveling machine (Paragraph [0091], “If the detected position and the reported position correspond within an acceptable tolerance, a level of verification of the reported UAV is established. If the detected position and the reported position do not correspond within an acceptable level of tolerance, the reported UAV position may be inaccurate. In this situation, further procedures may be instituted, as desired for the implementation, to address the unverified or disputed reported UAV position,” here the system is checking for a difference between a detected/extracted operation state and a reported/transmitted operation state to determine a soundness of the positioning of the vehicle)
and set the verification point when data deviating from the time correlation is observed (Paragraph [0215], “The procedures described above relative to the one or more processors of the first vehicle and the one or more processors of the second vehicle may be performed multiple times. The number of times that these procedures must be performed may be determined by a degree of synchronization between the one or more processors of the first vehicle and the one or more processors of the second vehicle. Unless a high degree of synchronization is present, multiple ToF measurements may be necessary. In cases of less than ideal synchronization, it may be known to perform three or more ToF measurements.”) (Paragraph [0244], “The signal quality as described herein may be any signal quality including, but not limited to any of a signal strength, a time stamp, a ToF, or any combination thereof.”) (Paragraph [0096], “a ToF operation is performed between the UAV 502 and the base station 504. An expected ToF may be determined based on the calculated distance between the reported position of the UAV 502 and the known position of the base station at 504 using a distance derived by equation (1) and the speed of light, such as 299,792,458 m/s. Using a ToF transmission, a measured ToF between the UAV 502 and the base station 504 may be determined. The expected ToF and measured ToF may be compared. If the expected ToF and measured ToF are within a reasonable tolerance,” here the flight path is correlated with a time of flight measurement which can be used to verify the position of the machine based on the synchronization of the ToF measurements) (Paragraph [0423], “wherein the one or more processors are further configured to determine a discrepancy between the determined first position and first orientation, and the received position of the orientation of the remote signal source relative to at least one of the at least three antennas; and if the discrepancy is greater than a predetermined threshold, redetermine the first position and first orientation.”).
Ohno and Ghosh are analogous art as they are both generally related to systems for controlling autonomous machines.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include the verification point at which the second autonomous traveling machine is recognizable by the first autonomous traveling machine in the second traveling route and a verification unit configured to compare an operation state transmitted from the second autonomous traveling machine at the verification point with the operation state extracted by the extraction unit to verify soundness of control on the second autonomous traveling machine and set the verification point when data deviating from the time correlation is observed of Ghosh in the system for controlling autonomous machines of Ohno with a reasonable expectation of success in order to improve the safety and security of the system by detecting a positional irregularity and performing appropriate actions to mitigate the effects of the erroneous system (Paragraph [0091], “In this situation, further procedures may be instituted, as desired for the implementation, to address the unverified or disputed reported UAV position. Under such circumstances, further information from the UAV (202 or 302) may be disregarded; the UAV (202 or 302) may be identified as an attacker or spoofer, and/or the UAV (202 or 303) may be disabled”).
However, while the combination teaches using a vehicle to determine the position of a second vehicle and verify that position against a reported position, the combination does not explicitly teach extract an operation state of the first autonomous traveling machine from the second surrounding situation data and compare an operation state transmitted from the first autonomous traveling machine with the extracted operation state of the first autonomous traveling machine to verify a soundness of control of the first autonomous traveling machine based on whether there is a difference between the extracted operation state of the first autonomous traveling machine and the transmitted operation state transmitted from the first autonomous traveling machine, thereby allowing the first autonomous traveling machine and the second autonomous traveling machine to monitor each other.
Guo teaches a location data correction service for connected vehicles wherein correction service is serverless and provided by one or more connected vehicles, connected vehicles form clusters of interconnected vehicles (e.g., via vehicle-to-everything, i.e., “V2X”) that are located at a similar geographic location including
extract an operation state of the first autonomous traveling machine from the second surrounding situation data (Paragraph [0112], “the collaborative location data includes digital data that describes, for each vehicle or other object in the roadway environment, a fusion of all the digital data received for this particular vehicle or object. For example, for a particular vehicle, the collaborative location data 172 for this vehicle describes a fusion of the self-reported location data for this vehicle, the location of this vehicle as determined by the other vehicles, and the location of this vehicle as determined by the operation center from the angle data and the distance data for this vehicle,” here the system is extracting data regarding each vehicle in an area from data received from all of the vehicles in the area, fusing all of the digital data for all vehicles including the location/extracted operation state determined by other vehicles)
and compare an operation state transmitted from the first autonomous traveling machine with the extracted operation state of the first autonomous traveling machine to verify a soundness of control of the first autonomous traveling machine based on whether there is a difference between the extracted operation state of the first autonomous traveling machine and the transmitted operation state transmitted from the first autonomous traveling machine (Paragraph [0112], “Variances between the self-reported location for this vehicle and the collaborative location data for this vehicle may be referred to as a “location error,”” here the system is comparing the operating state transmitted from each vehicle to the detected state determined/extracted from other vehicle data in order to determine a location error/soundess based on the difference)
thereby allowing the first autonomous traveling machine and the second autonomous traveling machine to monitor each other (Paragraph [0112], “the collaborative location data includes digital data that describes, for each vehicle or other object in the roadway environment, a fusion of all the digital data received for this particular vehicle or object. For example, for a particular vehicle, the collaborative location data 172 for this vehicle describes a fusion of the self-reported location data for this vehicle, the location of this vehicle as determined by the other vehicles, and the location of this vehicle as determined by the operation center from the angle data and the distance data for this vehicle,” here all vehicles in the vicinity are reporting location data and sensor data indicating extracted positions, allowing all of the vehicles to monitor each other).
Ohno, Ghosh, and Guo are analogous art as they are all generally related to systems for controlling autonomous machines.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include extract an operation state of the first autonomous traveling machine from the second surrounding situation data and compare an operation state transmitted from the first autonomous traveling machine with the extracted operation state of the first autonomous traveling machine to verify a soundness of control of the first autonomous traveling machine based on whether there is a difference between the extracted operation state of the first autonomous traveling machine and the transmitted operation state transmitted from the first autonomous traveling machine, thereby allowing the first autonomous traveling machine and the second autonomous traveling machine to monitor each other of Guo in the system for controlling autonomous machines of Ohno and Ghosh with a reasonable expectation of success in order to improve the safety of the roadway by allowing a plurality of vehicles to all monitor each other for soundness of control based on detected and reported positions (Paragraph [0026], “In this way, the serverless ad-hock vehicular network is operable to improve the operation of the legacy vehicle, which in turn increases the safety of the sensor rich vehicles that are traveling in a vicinity of the legacy vehicle.”).
Regarding claim 2, the combination of Ohno, Ghosh, and Guo teaches the system as discussed above in claim 1, Ohno further teaches wherein the first traveling route and the second traveling route are given from the same operation management system, which is a computer (Figure 1 shows a single operation management device 50 in communication with both a first vehicle and a second vehicle).
Regarding claim 3, the combination of Ohno, Ghosh, and Guo teaches the system as discussed above in claim 1, however Ohno does not explicitly teach wherein the extraction unit calculates, based on the first and second traveling routes and the first surrounding situation data, the verification point at which the second autonomous traveling machine is recognizable by the first autonomous traveling machine.
Ghosh further teaches wherein the processor is configured to calculate, based on the first and second traveling routes and the first surrounding situation data, the verification point at which the second autonomous traveling machine is recognizable by the first autonomous traveling machine (Paragraph [0068], “The one or more processors 102p may be configured, for example, to provide a flight path based at least on a current position of the unmanned aerial vehicle 100 and a target position for the unmanned aerial vehicle 100.”) (Paragraph [0088], “The approximate position of the UAV 202 may correspond to an overlapping region corresponding to an assumed path of travel from each of the three base stations along a path corresponding to the detected angles of arrival.” here the system is using the determined flight path/path of travel to determine an expected location of the vehicle where it will be detectable, while the system here is reciting the use of base stations, the system can similarly use other vehicles as recited by Paragraph [0086]).
Ohno and Ghosh are analogous art as they are both generally related to systems for controlling autonomous machines.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include wherein the processor is configured to calculate, based on the first and second traveling routes and the first surrounding situation data, the verification point at which the second autonomous traveling machine is recognizable by the first autonomous traveling machine of Ghosh in the system for controlling autonomous machines of Ohno with a reasonable expectation of success in order to improve the safety and security of the system by detecting a positional irregularity and performing appropriate actions to mitigate the effects of the erroneous system (Paragraph [0091], “In this situation, further procedures may be instituted, as desired for the implementation, to address the unverified or disputed reported UAV position. Under such circumstances, further information from the UAV (202 or 302) may be disregarded; the UAV (202 or 302) may be identified as an attacker or spoofer, and/or the UAV (202 or 303) may be disabled”).
Regarding claim 5, the combination of Ohno, Ghosh, and Guo teaches the system as discussed above in claim 1, however Ohno does not explicitly teach wherein the processor is configured to when it is determined that the second autonomous traveling machine is not in a normal control state as a result of verifying the soundness of the control the second autonomous traveling machine, the decrease reliability of data related to the operation state transmitted from the second autonomous travelling machine.
Ghosh further teaches wherein the processor is configured to when it is determined that the second autonomous traveling machine is not in a normal control state as a result of verifying the soundness of the control the second autonomous traveling machine, the decrease reliability of data related to the operation state transmitted from the second autonomous travelling machine (Paragraph [0091], “If the detected position and the reported position correspond within an acceptable tolerance, a level of verification of the reported UAV is established. If the detected position and the reported position do not correspond within an acceptable level of tolerance, the reported UAV position may be inaccurate. In this situation, further procedures may be instituted, as desired for the implementation, to address the unverified or disputed reported UAV position”).
Ohno and Ghosh are analogous art as they are both generally related to systems for controlling autonomous machines.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to include wherein the processor is configured to when it is determined that the second autonomous traveling machine is not in a normal control state as a result of verifying the soundness of the control the second autonomous traveling machine, the decrease reliability of data related to the operation state transmitted from the second autonomous travelling machine of Ghosh in the system for controlling autonomous machines of Ohno with a reasonable expectation of success in order to improve the safety and security of the system by detecting a positional irregularity and performing appropriate actions to mitigate the effects of the erroneous system (Paragraph [0091], “In this situation, further procedures may be instituted, as desired for the implementation, to address the unverified or disputed reported UAV position. Under such circumstances, further information from the UAV (202 or 302) may be disregarded; the UAV (202 or 302) may be identified as an attacker or spoofer, and/or the UAV (202 or 303) may be disabled”).
Regarding claim 6, the combination of Ohno, Ghosh, and Guo teaches the system as discussed above in claim 1, Ohno further teaches an autonomous control system comprising (Paragraph [0050], "The vehicle management system 100 includes: a plurality of vehicles 10 capable of traveling autonomously; a navigation management device (which hereafter may simply be referred to as the “management device”) 50 configured to manage navigation of the plurality of vehicles 10")
a first operation management system, which is a first computer, configured to transmit data of a first traveling route, a second operation management system, which is a second computer configured to transmit data of a second traveling route (Paragraph [0122], “FIG. 6 is referenced again. Each AGV 10 and the terminal device 20 may be connected e.g. in a one-to-one relationship to perform communications compliant with the Bluetooth standards (registered trademark) therebetween.”)
a first autonomous traveling machine (Paragraph [0051], "The vehicle management system 100 may include three or more vehicles 10. In this embodiment, the vehicle 10 is an automated guided vehicle (AGV). In the following description, the vehicle 10 may also be referred to as the “AGV 10”.”)
configured to recognize a surrounding situation to transmit first surrounding situation data (Paragraph [0055], "Each vehicle 10 has a function of detecting an obstacle on the traveling path and a function of notifying presence of the detected obstacle to the outside.")
transmit an own operation state (EXAMINERS NOTE: Here the examiner refers to the specification to interpret “operation state”, paragraph [0018] recites “Hereinafter, the own position, traveling direction, speed, and posture will be collectively referred to as an operation state,” therefore “operation state” is interpreted as traveling information for the vehicle) (Paragraph [0062], "As a result, if the vehicle 10 has found a traveling path to the position of the next target marker, the vehicle 10 may transmit the obstacle avoidance path (i.e., the altered traveling path) to the management device 50,” here the system is transmitting an avoidance path which includes at least position, direction, speed and therefore is transmitting an operation state)
and autonomously travel on a given first traveling route based on the first surrounding situation data (Paragraph [0055], "The controller 14a causes the vehicle 10 to travel along the traveling path determined by the processing circuit 51 by controlling a driving device which is not shown.")
a second autonomous traveling machine (Paragraph [0051], "The vehicle management system 100 may include three or more vehicles 10. In this embodiment, the vehicle 10 is an automated guided vehicle (AGV). In the following description, the vehicle 10 may also be referred to as the “AGV 10”.”)
being configured to recognize a surrounding situation to transmit second surrounding situation data (Paragraph [0055], "Each vehicle 10 has a function of detecting an obstacle on the traveling path and a function of notifying presence of the detected obstacle to the outside.")
transmit an own operation state (EXAMINERS NOTE: Here the examiner refers to the specification to interpret “operation state”, paragraph [0018] recites “Hereinafter, the own position, traveling direction, speed, and posture will be collectively referred to as an operation state,” therefore “operation state” is interpreted as traveling information for the vehicle) (Paragraph [0062], "As a result, if the vehicle 10 has found a traveling path to the position of the next target marker, the vehicle 10 may transmit the obstacle avoidance path (i.e., the altered traveling path) to the management device 50,” here the system is transmitting an avoidance path which includes at least position, direction, speed and therefore is transmitting an operation state)
and autonomously travel on a given second traveling route based on the second surrounding situation data (Paragraph [0055], "The controller 14a causes the vehicle 10 to travel along the traveling path determined by the processing circuit 51 by controlling a driving device which is not shown.")
the safety management system according to claim 1 (EXAMINERS NOTE: Here see the claim 1 rejection above for the rejection of the safety management system comprising extraction unit and verification unit as taught by the combination of the Ohno and Ghosh references)
wherein the safety management system transmits a first safety ensuring operation instruction related to the first autonomous traveling machine and a second safety-ensuring operation instruction related to the second autonomous traveling machine to each of the first and second autonomous traveling machines (Paragraph [0061], “Through the above-mentioned operation, each vehicle 10 can smoothly travel along a new path without being affected by the obstacle. When a vehicle 10 finds an obstacle, an instruction indicating an avoidance path for avoiding the obstacle is transmitted from the management device 50. Thus, navigation control by the vehicle management system can be made smoother.”)
and wherein each of the processors of the first and second autonomous traveling machines is configured to determine whether there is a contradiction or inconsistency between the first and second safety-ensuring operation instructions (Paragraph [0157], "The localization device 14e identifies the AGV's position (x, y, θ) on the map data M by matching the local map data (or sensor data) generated from the scanning results of the laser range finder 15 against wider-range map data M. The localization device 14e generates “reliability” data indicating the degree of coincidence of the local map data with the map data M,” here the system is using the verification position information according to the determined path in order to compare the sensed position and determine an inconsistency in control of the vehicle)
and give a notification of an abnormality of the safety management system when determining that there is a contradiction or inconsistency (Paragraph [0157], “The terminal device 20 or the navigation management device 50 may receive the respective data of the AGV's position (x, y, θ) and the reliability and may display the data on a display that is built therein or connected thereto.”).
EXAMINERS NOTE: Regarding claim 6 the limitations of determining a contradiction or inconsistency is taught by Ohno in the form of the reliability determination. The examiner would like to note that these limitations are also taught by the Ghosh reference which transmits a flight path/safety ensuring instruction to the vehicles and determines inconsistency in the vehicle by comparing the detected position of the vehicle to the reported position of the vehicle based on the transmitted flight paths.
Regarding claim 8, claim 8 is similar in scope to claims 1 and 6, and therefore is rejected under similar rationale.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Lee (US-11898851) teaches an apparatus for estimating a location of a vehicle including, a communication unit configured to receive, from an information providing vehicle, identification information and location information on a driving vehicle in a vicinity of the information providing vehicle, a weighted value obtaining unit configured to obtain a weighted value representing accuracy of the location information based on the received identification information and a location estimating unit configured to estimate a location of the driving vehicle by applying the weighted value to the location information. Ito (US-20200386566) teaches a vehicle in a self-position sharing system includes: a processor configured to estimate a self-position of the vehicle with measurement accuracy higher than that of the terminal at a predetermined period, determine whether or not measurement accuracy of a self-position by the terminal decreases, set a notification frequency of notifying the terminal of an estimated self-position of the vehicle to a first frequency when the measurement accuracy does not decrease, set the notification frequency to a second frequency higher than the first frequency when the measurement accuracy decreases; and notify the terminal of an estimated self-position of the vehicle with the set notification frequency. Nishimura (US-20200041657) teaches estimates a calculation accuracy for the first position information in a road section on a road map based on one or more pieces of difference information in which one or more positions indicated by the second position information corresponding to the difference information are within the road section and to output the calculation accuracy for the first position information in the road section.
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/CHRISTOPHER GEORGE FEES/Primary Examiner, Art Unit 3662
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