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
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 07/17/2026 has been entered.
Status of Claims
The following is non-final rejection in response to the arguments/amendment present in the response after final action filed on 06/25/2026.
Claims 1-25 are pending and have been examined.
Claims 1-25 are amended directly or a via a claim they depend from.
Claims 1-25 are rejected.
Response to Arguments
Applicant’s argument’s and corresponding amendments, see pages 7-9, filed on 06/25/2026, have been fully considered and are addressed as follows.
Regarding the Provisional Double Patenting Rejection: Applicant’s amendment to independent claim 16, and the status of independent claim 1 of US 12656784 B2 (Application # 18/760,229) has rendered the previous rejection moot. Accordingly, the rejection has been withdrawn.
Regarding the Claim Rejections under 35 § USC 103: Applicant’s arguments/amendments
have overcome all previously applied rejections. However, after further search and consideration, new grounds of rejections that do not rely upon an issue particularly challenged by the Applicant have been respectfully made in response to the amendments. The new grounds can be viewed in the subsequent, Claim Rejections - 35 USC § 103, section for applicant’s consideration.
The independent claims are rejected under 35 U.S.C. 103 as being unpatentable over Van De Velde et al. (US 2024/0310860 A1, hereinafter Van De Velde) in view of Dembinski et al., (US 10,579,073 B2, hereinafter, Dembinski) further in view of Gupta et al., (US 2024/0377825 A1, hereinafter Gupta) further in view of Mudalige. (US 8,676,466 B2, hereinafter Mudalige) Due to the nature of the rejection comprising numerous references, the Examiner of which applied due to the perceived large breadth of the independent claims, Applicant is encouraged to contact Examiner ALEXANDER V. GENTILE, whose telephone number is (703)756-1501, to schedule an interview in order to facilitate compact prosecution.
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 1-6, 19-20, and 23-25 are rejected under 35 U.S.C. 103 as being unpatentable over Van De Velde et al. (US 2024/0310860 A1, hereinafter Van De Velde) in view of Dembinski et al., (US 10,579,073 B2, hereinafter, Dembinski) further in view of Gupta et al., (US 2024/0377825 A1, hereinafter Gupta) further in view of Mudalige. (US 8,676,466 B2, hereinafter Mudalige)
Claim 1 Discloses: (Currently Amended)
“A method of managing vehicle movement through an operating environment,”
Van De Velde teaches, (Abstract, Lines 1-3) “Systems and methods for controlling or guiding one or more automated vehicles and/or people (VOP) in an environment using virtual approved pathways (VAPs),” and that, (Paragraphs [0021] & [0255]) “FIG. 5 is a schematic representation of an exemplary graphical user interface screen depicting a portion of the virtual representation while determining an optimal navigation plan for the VOP… FIG. 5 depicts generating optimal trajectories based on zones, properties and rules associated with the zones and the VOPs 112. In an example, The VOPs 112 while executing a certain task are aware about No-Go Zones 402A (to be navigated around may be areas around certain obstacles such as equipment, but also open areas) and the like.”
“the method comprising: moving a first vehicle and a second vehicle individually through a first portion of the operating environment; moving the first vehicle and the second vehicle synchronously together as a group through a second portion of the operating environment;
Van De Velde does not teach an explicit first portion of the operating environment wherein a first a second vehicle must move individually and second portion of the operating environment wherein the first vehicle and the second vehicle synchronously. However, Van de Velde does teach demarcating travelable zones with particular rules associated with them, that may for example, dictate the acceptable pathing of each vehicle, which may be influenced by whether another vehicle is present in the environment.
Van De Velde teaches, (Paragraph [0115]) “a specifically delineated area (in 2D or 3D space) within an overall Environment. A Zone is characterized by its boundaries and is typically defined for specific functions, usage, or characteristics within a larger setting … A Zone may have certain Properties and/or Rules associated with it (to e.g., help in establishing control, safety, and efficiency by segmenting larger spaces into manageable, functional areas),” wherein, (Paragraph [0157], Lines 21-29) “depending on the circumstances, zones, pathways, stations, and even other VOPs 112, the VOPs 112 may inherit or overrule each other's properties and/or rules. For example, certain zones may have rules that take priority over (“overrule”) certain rules associated with certain pathways, pathway sections, or stations that fall within those zones. For example, all path sections within a certain zone may be off-limits to a certain class of the VOPs 112.” Therefore, certain zones may accept vehicles while limiting and/or rerouting others.
Van De Velde additionally teaches, (Paragraph [0179], Lines 6-14) “the control system 102 is configured to actively launch one or more VOPs 112 to the VAP section and to specific sections within the environment 106 for validating the identified current state, re-determine the plurality of environmental conditions and re-transmit the first set of parameters at real-time. The one or more VOPs 112 that are determined to be available and capable of performing the task, navigate and reach the destination point.” Therefore, VOPs are additionally capable of traveling together as a group through the environment.
Dembinski does explicitly teach a first portion of the operating environment wherein a first vehicle and second vehicle must move individually.
Dembinski is relevant to the Applicant’s disclosure due to its teachings of designating zones for amusement ride vehicles that dictate whether said vehicles travels individually or synchronously as a group.
Dembinski teaches, (Abstract, Lines 1-3) “A ride control system includes a central controller configured to synchronize movements of separate groups of ride vehicles along a path,” wherein, (Page 12, Column 12, Lines 48-57) “For example, each ride vehicle 16 of the virtual train 52 may travel together (e.g., during a first instance 111) along the path 20 until the virtual train 52 reaches the split-path portion 110. Once the virtual train 52 reaches the split-path portion 110, one or more of the ride vehicles 16 may travel along the path 20a while the other ride vehicles 16 travel along the path 20b (e.g., during a second instance 113). Indeed, any suitable number or subset of the ride vehicles 16 may travel along either the path 20a or the path 20b.”
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Dembinski additionally does explicitly teach wherein a second portion of the environment wherein the first vehicle and the second vehicle synchronously.
Dembinski teaches, (Page 13, Column 11, Lines 3-6) “when in the loading area 54 (FIG. 2), the central controller 22 may assign schedules to the ride vehicles 16 such that the ride vehicles 16 travel within a certain virtual train 52.”
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 automated vehicle control system capable of applying different travel rules to a plurality of vehicles depending on what zone they are in as taught by Van De Velde, with the teachings of separating zones that determine whether vehicles travel with one another in the context of an amusement ride as taught by Dembinski, in order to yield predictable results.
Combining the references would yield the benefits of being able to modify the entertainment experience in the context of an amusement park by varying the positioning and/or platooning of vehicles. As Dembinski describes, (Pag 13, Column 12, Lines 66-67 & Page 14, Column 13, Lines 1-2) “After traveling through the split-path portion 110, the ride vehicles 16 may converge or rejoin the ride vehicles 16 in a different order than before the split -path portion 110, as shown,” and that, (Page 13, Column 11, Lines 40-45) “some ride vehicles 16 may have different experiences along the path 20 according to their relative position. For example, the ride vehicles 16 may experience different special effects or travel along different portions of the path 20 based at least on their relative position within the virtual train 52,” and further that, (Page 13, Column 12, Lines 18-23) “In another example, in contrast to trains or longer coupled vehicles that may experience irregularity in globally-applied motion effects (e.g., more intense effects at the ends relative to the middle of the train), the virtual trains 52 may be capable of providing more uniform experiences, if desired, during motion effects.”
“comparing, by the first vehicle and using a virtual map, a position of the first vehicle to a position of an obstacle in the first portion or the second portion; querying, by the first vehicle, the virtual map for a characteristic of the obstacle; and adjusting, … a trajectory of the first vehicle to avoid the obstacle based on a clearance envelope determined from the characteristic.”
Van De Velde and Dembinski do not explicitly teach the preceding limitations. However, Van de Velde does teach the following.
Van De Velde teaches, (Paragraph [0161], Lines 9-12) “The VOPs 112 are able to enhance their navigational abilities, by combining SLAM (“Simultaneous Locating and Mapping”) methods with RTLS-based localization and navigation methods.” Therefore, Van De Velde teaches comparing, by the first vehicle and using a virtual map, a position of the first vehicle to a position of an obstacle.
Van De Velde additionally teaches, (Paragraph [0147], Lines 23-32) “The data collected may be used to determine whether or not a certain trajectory is (for example) feasible, safe, effective, and/or efficient, or anticipated to be (for example) feasible, safe, effective, and/or efficient for the intended activity and/or objective by one or more specific VOPs 112 at a certain current or future time, depending on possibly dynamic circumstances (e.g. actual or expected or predicted congestion or obstacles in certain areas of the environment 106,” wherein for example, (Paragraph [0148], Lines 8-16) “The certain restrictions may include allowing directionality (possibly further restricted based on certain circumstances, e.g. whether a VOP 112 is carrying a Load, or pulling/pushing a Cart, or not), and height restrictions (e.g. certain VOPs 112 fit under certain racks or conveyors, while others VOPs 112 may not or; a VOP 112 may fit and be able to travel under a certain obstacle while empty, but not while carrying a Load),” and that (Paragraph [0146], Lines 1-9) “the VAP may be, in whole or in part, parallel to other VAPs or VAP sections, possibly created by the control system 102, on a temporary basis to help the VOP 112 avoid an obstacle, whereby the distance between the parallel VAPs or VAP sections may be defined and adjusted dynamically by the control system 102. Further, the VAP may be changed dynamically, and possibly just-in-time, by the control system 102, as far as the routes or properties or rules are concerned.”
Therefore, the introduction of a particular obstacle causes the dynamic adjustment of routing per vehicle based upon the applicable dimensions and/or clearance envelope, such as having enough clearance to travel underneath an obstacle, which differs per vehicle. Therefore, the applicable routing adjustment per vehicle may vary.
However, Van De Velde does not explicitly teach querying, by the first vehicle, the virtual map for a characteristic of the obstacle; and adjusting, by the first vehicle and separate from the second vehicle, a trajectory of the first vehicle to avoid the obstacle based on a clearance envelope determined from the characteristic.
Gupta does teach querying, by the first vehicle, the virtual map for a characteristic of the obstacle; and adjusting a trajectory of the first vehicle to avoid the obstacle based on a clearance envelope determined from the characteristic.
Despite being directed to an autonomous vehicle traveling on a highway, Gupta is relevant to the Applicant’s disclosure due to its teachings regarding querying a virtual map.
Gupta teaches, in regards to the traveling autonomous vehicle, (Abstract, Lines 1-4) “Methods, systems, and non-transitory computer-readable media are configured to perform operations comprising determining map data and detection data for an area in an environment,” wherein, (Paragraph [0060]) “In addition, the prediction and planning module 616 can generate a motion plan for the vehicle 800 that navigates the vehicle 600 in relation to the predicted location and movement of other obstacles so that collisions are avoided,” and that in regards to, “conventional approaches, navigation of a vehicle based on use of a map and detection of obstacles poses various technological challenges,” (Paragraph [0025], Lines 22-31) “For example, an autonomous system of a vehicle can navigate a highway that goes under an overpass. The autonomous system of the vehicle may not be configured to detect the height of the overpass. Because the autonomous system of the vehicle is not configured to detect the height of the overpass, the autonomous system relies on information in a map to determine whether the height of the overpass, or the clearance under the overpass, is sufficient for the vehicle to safely navigate under the overpass.”
Gupta additionally teaches, (Paragraph [0027], Lines 23-28) “The autonomous system can provide the detection data captured at the environment, such as the clearance under the overpass, to automatically update the map. The updated map, for example, can be used later by an autonomous system of another vehicle to safely navigate the environment,” and that, (Paragraph [0064], Lines 18-20) “The processed data can be selectively communicated to the fleet, including vehicle 600, to assist in navigation of the fleet as well as the vehicle 600 in particular.”
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 system of Van De Velde which determines feasible trajectories for an autonomous vehicle that may avoid obstacles, such as obstacles which create height concerns, with the conventional approach of querying a virtual map for obstacle characteristic information to determine said clearance as taught by Gupta, in order to yield predictable results.
Combining the references yield the well-known benefits of detection redundancy for identifying obstacles that could cause collision by, for example, providing map data to a vehicle that does not have sensor data as an option. As Gupta describes, (Paragraph [0025, Lines 26-31) Because the autonomous system of the vehicle is not configured to detect the height of the overpass, the autonomous system relies on information in a map to determine whether the height of the overpass, or the clearance under the overpass, is sufficient for the vehicle to safely navigate under the overpass.”
Combining the references may additionally yield well known benefits in the situation where an autonomous vehicle has multiple means for determining a change in the surroundings by implementing a comparison between a sensed environment and that which is queried from map data. As Gupta describes, (Paragraph [0026], Lines 24-27) “A change in an environment can be detected based on a comparison between information in the map and detection data associated with the environment.”
“adjusting, by the first vehicle and separate from the second vehicle, a trajectory of the first vehicle to avoid the obstacle”
Vane De Velde, Dembinski, and Gupta do not explicitly teach adjusting, by the first vehicle and separate from the second vehicle, a trajectory of the first vehicle to avoid the obstacle.
Mudalige does explicitly teach adjusting, by the first vehicle and separate from the second vehicle, a trajectory of the first vehicle to avoid the obstacle.
Mudalige is relevant to the Applicant’s disclosure due to its teachings of the state of the art, specifically regarding trajectory behavior for a platoon encountering an obstacle.
Mudalige teaches, (Page 37, Column 31, Lines 13-41) “Use of a platoon desirable envelope can facilitate a number of navigation functions of the platoon. For example, the desirable envelope can be taken into account … Obstacle detection and avoidance programs can utilize a desirable envelope in a number of ways. For example, if an obstacle is detected in a particular lane to interfere with some portion of the platoon, the formation can be adjusted to make certain that the desirable envelope is not violated by the obstacle. In the event that an obstacle is dynamic, for example, a vehicle in front of the platoon slowing and indicating a turn outside of the path of the platoon, only vehicles that will have minimum desirable ranges predictably impacted by the dynamic obstacle need to be adjusted. If a column of five vehicles exist in the particular lane, but a prediction is made that only the first two vehicles in the column will be affected by the dynamically changing obstacle, room can be made in the formation for the two vehicles to switch lanes, while the remaining three vehicles in the column can be maintained in their current positions in the formation. Upon the change, the platoon desirable envelope can be reformulated, and reactions can be made if the dynamically changing obstacle fails to follow the predicted behavior.”
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 automated vehicle control system capable of both applying different travel rules to a plurality of vehicles depending on what zone they are in and maintaining clearance envelopes between vehicles and obstacles as taught by Van De Velde, with the teachings of separating zones that determine whether vehicles travel with one another for entertainment outcomes in the context of an amusement ride as taught by Dembinski, the virtual map obstacle information querying which may be applied to the context of a vehicle platoon as taught by Gupta, and the platoon obstacle avoidance methodology of individually moving vehicles on independent trajectories as taught by Mudalige, in order to yield predictable results.
Combining the references would yield the benefits of saving computation resources/energy for moving vehicles upon facing an obstacle by only moving the vehicles that are effected. As Mudalige describes, (Page 37, Column 31, Lines 13-41) “only vehicles that will have minimum desirable ranges predictably impacted by the dynamic obstacle need to be adjusted … Upon the change, the platoon desirable envelope can be reformulated, and reactions can be made if the dynamically changing obstacle fails to follow the predicted behavior,” and further describes, (Page 37, Column 31, Lines 4-7) “In this way, the use of a platoon desirable envelope in the standard V2V message reduces the collision avoidance process complexity and computational load for all V2X equipped vehicles.”
Claim 2 Discloses: (Previously Presented)
“The method of claim 1, further comprising updating, by the first vehicle and on the virtual map, the position of the first vehicle.”
Van de Velde teaches, (Paragraph [0161], Lines 9-12) “The VOPs 112 are able to enhance their navigational abilities, by combining SLAM (“Simultaneous Locating and Mapping”) methods with RTLS-based localization and navigation methods.”
Claim 3 Discloses: (Previously Presented)
“The method of claim 1, further comprising coordinating, by one of the first vehicle or the second vehicle, movement of the second vehicle with movement of the first vehicle through the operating environment.”
Van De Velde teaches, (Paragraph [0179], Lines 6-14) “the control system 102 is configured to actively launch one or more VOPs 112 to the VAP section and to specific sections within the environment 106 for validating the identified current state, re-determine the plurality of environmental conditions and re-transmit the first set of parameters at real-time. The one or more VOPs 112 that are determined to be available and capable of performing the task, navigate and reach the destination point,” and that, (Paragraph [0161], Lines 5-9) “The map or maps created in such way, may then be used for the VOP 112 and/or any other VOPs 112 within the same environment 106, which may share the map information through the control system 102.”
Claim 4 Discloses: (Previously Presented)
“The method of claim 1, further comprising: detecting a second obstacle in the operating environment; determining the second obstacle is not represented in the virtual map; adding the second obstacle to the virtual map;”
Van De Velde teaches, (Paragraph [0161], Lines 5-12) “The map or maps created in such way, may then be used for the VOP 112 and/or any other VOPs 112 within the same environment 106, which may share the map information through the control system 102. The VOPs 112 are able to enhance their navigational abilities, by combining SLAM (“Simultaneous Locating and Mapping”) methods with RTLS-based localization and navigation methods,” and that, (Paragraph [0186], Lines 11-14) “The control system 102 may update the navigation plan if environmental conditions change (for example obstacles appear).”
“adjusting, by the first vehicle, a second trajectory of the first vehicle to avoid the second obstacle; and adjusting, by the second vehicle, a trajectory of the second vehicle to avoid the second obstacle.”
Van de Velde teaches, (Paragraph [054], Lines 8-18) “Specifically, the control system 102, while directing or guiding a VOP 112 along planned trajectories, may include identifying and avoiding possible collision with fixed or mobile obstacles, including other VOPs 112. The control system 102 continuously evaluates and replans the planned trajectories, and associated navigation plans, for all VOPs 112 active in the environment 106, to avoid possible collision, while enabling the VOPs 112 to continue to travel towards their intended destination points, such as stations or targets, in line with all the applicable rules and/or objectives.”
Claim 5 Discloses: (Previously Presented)
“The method of claim 1, further comprising: detecting, by the first vehicle, an environmental feature of the operating environment; and determining, by the first vehicle, the position of the first vehicle based on the detected environmental feature.”
Van De Velde teaches, (Paragraph [0159], Lines 1-3) “In some preferred embodiment, the VOP 112 is able to create at least one Simultaneous Locating and Mapping (SLAM) map of the environment 106,” and that, (Paragraph [0160], Lines 8-15) the VOP 112 maps the environment 106, typically collecting data using one or more LiDAR sensors or possibly using vision cameras or other sensors that are able to map certain aspects and features of the environment 106 in such way that an VOP 112 should be able to recognize certain environmental features at some later time, allowing the VOP to determine its position within the environment 106.”
Van De Velde additionally teaches, (Paragraph [0153], Lines 19-26) “the control system 102 is configured to determine the plurality of environmental conditions, the current position of the destination point, the predicted position of the destination point, and the possible movements of the destination point. The plurality of environmental conditions is determined using one or more sensors 114 present within the environment 106. The one or more sensors 114 may include sensors associated with the one or more VOPs 112,” wherein, (Paragraph [0153], Lines 14-15) “the control system 102 is configured to continuously monitor the current location of the VOP 112.”
Claim 6 Discloses: (Previously Presented)
“The method of claim 5, further comprising validating, by the first vehicle, the virtual map based on the detected environmental feature.”
Van De Velde teaches, (Paragraph [0179], Lines 6-11) “Furthermore, the control system 102 is configured to actively launch one or more VOPs 112 to the VAP section and to specific sections within the environment 106 for validating the identified current state, re-determine the plurality of environmental conditions and re-transmit the first set of parameters at real-time.”
Claim 7 Discloses: (Previously Presented)
“The method of claim 1, wherein the virtual map is stored on at least one of the first vehicle or the second vehicle.”
Van De Velde teaches, (Paragraph [0092], Lines 7-13) “the Trajectory is the actual combination of the specific VAPs and/or VAP Sections chosen for a VOP to actually travel from one location to another. A Trajectory may be represented as a Virtual Element, by a computer system such as a Control System, on a digital representation of an Environment, such as a Map or Floor Plan or 3D rendering.”
Van De Velde additionally teaches, (Paragraph [0143], Lines 1-7) “the VAPs are virtual representations of approved routes within an environment 106, defined by a set of coordinates within a defined coordinate system. These routes act as a framework for the VOP 112 movement while allowing for adaptability based on specific VOP 112 capabilities and environmental conditions,” and that, (Paragraph [0144], Lines 1-4) “The control system 102 may store the VAPs, including both their Routes and associated properties and rules. This control system 102 may be located on-board an VOP 112 itself.”
Claim 8 Discloses: (Currently Amended)
“The method of claim 1, wherein the obstacle is the second vehicle or [[the]] a third vehicle, an element of the operating environment, or an undesired area of the operating environment.”
Van De Velde teaches, (Paragraph [0255]) “FIG. 5 depicts generating optimal trajectories based on zones, properties and rules associated with the zones and the VOPs 112. In an example, The VOPs 112 while executing a certain task are aware about No-Go Zones 402A (to be navigated around may be areas around certain obstacles such as equipment, but also open areas) and the like.”
Van De Velde additionally teaches, (Paragraph [0154], Lines 8-12) “the control system 102, while directing or guiding a VOP 112 along planned trajectories, may include identifying and avoiding possible collision with fixed or mobile obstacles, including other VOPs 112.”
Claim 9 Discloses: (Currently Amended)
“The method of claim 1, wherein the obstacle is undetectable to the first vehicle.”
Van De Velde teaches, (Paragraph [0202], Lines 1-8) “In various embodiments, the control system 102 may also perform one or more of: smoothing the trajectories (e.g. to comply with desired travel conditions), highlighting the portions of trajectories that are not feasible for specific classes of VOPs 112 due to geometric limitations of the VOP 112 (for example too sharp turn for turning radius of VOP 112) and/or under certain circumstances (for example meant to carry a wide load).” Therefore, the applicability of whether a route segment should be considered as an “obstacle” due to the vehicle being too large to make an applicable turn, is determined independently from the vehicle as part of the map information. The determination on whether a pathway is feasible is determined in the map by the class of VOP. As a non-limiting embodiment in Paragraph [0025] of Applicant’s disclosure describes, “In some embodiments, at least one obstacle 110 may be undetectable to the vehicle 112. In such embodiments, the presence of the obstacle 110 may be known to the vehicle 112 only by the virtual map 100.”
Claim 10 Discloses: (Currently Amended)
“A method of managing vehicle movement through an operating environment,”
Van de Velde teaches, (Abstract, Lines 1-3) “Systems and methods for controlling or guiding one or more automated vehicles and/or people (VOP) in an environment using virtual approved pathways (VAPs),” and that, (Paragraphs [0021] & [0255]) “FIG. 5 is a schematic representation of an exemplary graphical user interface screen depicting a portion of the virtual representation while determining an optimal navigation plan for the VOP… FIG. 5 depicts generating optimal trajectories based on zones, properties and rules associated with the zones and the VOPs 112. In an example, The VOPs 112 while executing a certain task are aware about No-Go Zones 402A (to be navigated around may be areas around certain obstacles such as equipment, but also open areas) and the like.”
“the method comprising: moving a first vehicle and a second vehicle individually through a first portion of the operating environment; moving the first vehicle and the second vehicle together as a group through a second portion of the operating environment;”
Van De Velde does not teach an explicit first portion of the operating environment wherein a first a second vehicle must move individually and second portion of the operating environment wherein the first vehicle and the second vehicle synchronously. However, Van De Velde does teach demarcating travelable zones with particular rules associated with them, that may for example, dictate the acceptable pathing of each vehicle, which may be influenced by whether another vehicle is present in the environment.
Van De Velde teaches, (Paragraph [0115]) “a specifically delineated area (in 2D or 3D space) within an overall Environment. A Zone is characterized by its boundaries and is typically defined for specific functions, usage, or characteristics within a larger setting … A Zone may have certain Properties and/or Rules associated with it (to e.g., help in establishing control, safety, and efficiency by segmenting larger spaces into manageable, functional areas),” wherein, (Paragraph [0157], Lines 21-29) “depending on the circumstances, zones, pathways, stations, and even other VOPs 112, the VOPs 112 may inherit or overrule each other's properties and/or rules. For example, certain zones may have rules that take priority over (“overrule”) certain rules associated with certain pathways, pathway sections, or stations that fall within those zones. For example, all path sections within a certain zone may be off-limits to a certain class of the VOPs 112.” Therefore, certain zones may accept vehicles while limiting and/or rerouting others.
Van De Velde additionally teaches, (Paragraph [0179], Lines 6-14) “the control system 102 is configured to actively launch one or more VOPs 112 to the VAP section and to specific sections within the environment 106 for validating the identified current state, re-determine the plurality of environmental conditions and re-transmit the first set of parameters at real-time. The one or more VOPs 112 that are determined to be available and capable of performing the task, navigate and reach the destination point.” Therefore, VOPs are additionally capable of traveling together as a group through the environment.
Dembinski does explicitly teach a first portion of the operating environment wherein a first vehicle and second vehicle must move individually.
Dembinski is relevant to the Applicant’s disclosure due to its teachings of designating zones for amusement ride vehicles that dictate whether said vehicles travels individually or synchronously as a group.
Dembinski teaches, (Abstract, Lines 1-3) “A ride control system includes a central controller configured to synchronize movements of separate groups of ride vehicles along a path,” wherein, (Page 12, Column 12, Lines 48-57) “For example, each ride vehicle 16 of the virtual train 52 may travel together (e.g., during a first instance 111) along the path 20 until the virtual train 52 reaches the split-path portion 110. Once the virtual train 52 reaches the split-path portion 110, one or more of the ride vehicles 16 may travel along the path 20a while the other ride vehicles 16 travel along the path 20b (e.g., during a second instance 113). Indeed, any suitable number or subset of the ride vehicles 16 may travel along either the path 20a or the path 20b.”
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Dembinski additionally does explicitly teach wherein a second portion of the environment wherein the first vehicle and the second vehicle synchronously.
Dembinski teaches, (Page 13, Column 11, Lines 3-6) “when in the loading area 54 (FIG. 2), the central controller 22 may assign schedules to the ride vehicles 16 such that the ride vehicles 16 travel within a certain virtual train 52.”
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 automated vehicle control system capable of applying different travel rules to a plurality of vehicles depending on what zone they are in as taught by Van De Velde, with the teachings of separating zones that determine whether vehicles travel with one another in the context of an amusement ride as taught by Dembinski, in order to yield predictable results.
Combining the references would yield the benefits of being able to modify the entertainment experience in the context of an amusement park by varying the positioning and/or platooning of vehicles. As Dembinski describes, (Pag 13, Column 12, Lines 66-67 & Page 14, Column 13, Lines 1-2) “After traveling through the split-path portion 110, the ride vehicles 16 may converge or rejoin the ride vehicles 16 in a different order than before the split -path portion 110, as shown,” and that, (Page 13, Column 11, Lines 40-45) “some ride vehicles 16 may have different experiences along the path 20 according to their relative position. For example, the ride vehicles 16 may experience different special effects or travel along different portions of the path 20 based at least on their relative position within the virtual train 52,” and further that, (Page 13, Column 12, Lines 18-23) “In another example, in contrast to trains or longer coupled vehicles that may experience irregularity in globally-applied motion effects (e.g., more intense effects at the ends relative to the middle of the train), the virtual trains 52 may be capable of providing more uniform experiences, if desired, during motion effects.”
“comparing, by a processor and using a virtual map, a position of the first vehicle to a position of an obstacle in the operating environment; querying, by the processor, the virtual map for a characteristic of the obstacle; and instructing, … a trajectory of the first vehicle to avoid the obstacle based on a clearance envelope determined from the characteristic.”
Van De Velde and Dembinski do not explicitly teach the preceding limitations. However, Van de Velde does teach the following.
Van de Velde teaches, (Paragraph [0161], Lines 9-12) “The VOPs 112 are able to enhance their navigational abilities, by combining SLAM (“Simultaneous Locating and Mapping”) methods with RTLS-based localization and navigation methods.” Therefore, Van De Velde teaches comparing, by the first vehicle and using a virtual map, a position of the first vehicle to a position of an obstacle.
Van de Velde additionally teaches, (Paragraph [0147], Lines 23-32) “The data collected may be used to determine whether or not a certain trajectory is (for example) feasible, safe, effective, and/or efficient, or anticipated to be (for example) feasible, safe, effective, and/or efficient for the intended activity and/or objective by one or more specific VOPs 112 at a certain current or future time, depending on possibly dynamic circumstances (e.g. actual or expected or predicted congestion or obstacles in certain areas of the environment 106,” wherein for example, (Paragraph [0148], Lines 8-16) “The certain restrictions may include allowing directionality (possibly further restricted based on certain circumstances, e.g. whether a VOP 112 is carrying a Load, or pulling/pushing a Cart, or not), and height restrictions (e.g. certain VOPs 112 fit under certain racks or conveyors, while others VOPs 112 may not or; a VOP 112 may fit and be able to travel under a certain obstacle while empty, but not while carrying a Load),” and that (Paragraph [0146], Lines 1-9) “the VAP may be, in whole or in part, parallel to other VAPs or VAP sections, possibly created by the control system 102, on a temporary basis to help the VOP 112 avoid an obstacle, whereby the distance between the parallel VAPs or VAP sections may be defined and adjusted dynamically by the control system 102. Further, the VAP may be changed dynamically, and possibly just-in-time, by the control system 102, as far as the routes or properties or rules are concerned.”
Therefore, the introduction of a particular obstacle causes the dynamic adjustment of routing per vehicle based upon the applicable dimensions and/or clearance envelope, such as having enough clearance to travel underneath an obstacle, which differs per vehicle. Therefore, the applicable routing adjustment per vehicle may vary.
However, Van de Velde does not explicitly teach querying, by the first vehicle, the virtual map for a characteristic of the obstacle; and adjusting, by the first vehicle and separate from the second vehicle, a trajectory of the first vehicle to avoid the obstacle based on a clearance envelope determined from the characteristic.
Gupta does teach querying, by the first vehicle, the virtual map for a characteristic of the obstacle; and adjusting a trajectory of the first vehicle to avoid the obstacle based on a clearance envelope determined from the characteristic.
Despite being directed to an autonomous vehicle traveling on a highway, Gupta is relevant to the Applicant’s disclosure due to its teaching regarding querying a virtual map.
Gupta teaches, in regards to the traveling autonomous vehicle, (Abstract, Lines 1-4) “Methods, systems, and non-transitory computer-readable media are configured to perform operations comprising determining map data and detection data for an area in an environment,” wherein, (Paragraph [0060]) “In addition, the prediction and planning module 616 can generate a motion plan for the vehicle 800 that navigates the vehicle 600 in relation to the predicted location and movement of other obstacles so that collisions are avoided,” and that in regards to, “conventional approaches, navigation of a vehicle based on use of a map and detection of obstacles poses various technological challenges,” (Paragraph [0025], Lines 22-31) “For example, an autonomous system of a vehicle can navigate a highway that goes under an overpass. The autonomous system of the vehicle may not be configured to detect the height of the overpass. Because the autonomous system of the vehicle is not configured to detect the height of the overpass, the autonomous system relies on information in a map to determine whether the height of the overpass, or the clearance under the overpass, is sufficient for the vehicle to safely navigate under the overpass.”
Gupta additionally teaches, (Paragraph [0027], Lines 23-28) “The autonomous system can provide the detection data captured at the environment, such as the clearance under the overpass, to automatically update the map. The updated map, for example, can be used later by an autonomous system of another vehicle to safely navigate the environment,” and that, (Paragraph [0064], Lines 18-20) “The processed data can be selectively communicated to the fleet, including vehicle 600, to assist in navigation of the fleet as well as the vehicle 600 in particular.”
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 system of Van De Velde which determines feasible trajectories for an autonomous vehicle that may avoid obstacles, such as obstacles which create height concerns, with the conventional approach of querying a virtual map for obstacle characteristic information to determine said clearance as taught by Gupta, in order to yield predictable results.
Combining the references yield the well-known benefits of detection redundancy for identifying obstacles that could cause collision by, for example, providing map data to a vehicle that does not have sensor data as an option. As Gupta describes, (Paragraph [0025, Lines 26-31) Because the autonomous system of the vehicle is not configured to detect the height of the overpass, the autonomous system relies on information in a map to determine whether the height of the overpass, or the clearance under the overpass, is sufficient for the vehicle to safely navigate under the overpass.”
Combining the references may additionally yield well known benefits in the situation where an autonomous vehicle has multiple means for determining a change in the surroundings by implementing a comparison between a sensed environment and that which is queried from map data. As Gupta describes, (Paragraph [0026], Lines 24-27) “A change in an environment can be detected based on a comparison between information in the map and detection data associated with the environment.”
“and instructing, separate from the second vehicle and by the processor, a trajectory of the first vehicle”
Vane De Velde, Dembinski, and Gupta do not explicitly teach adjusting, by the first vehicle and separate from the second vehicle, a trajectory of the first vehicle to avoid the obstacle.
Mudalige does explicitly teach adjusting, by the first vehicle and separate from the second vehicle, a trajectory of the first vehicle to avoid the obstacle.
Mudalige is relevant to the Applicant’s disclosure due to its teachings of the state of the art, specifically regarding trajectory behavior for a platoon encountering an obstacle.
Mudalige teaches, (Page 37, Column 31, Lines 13-41) “Use of a platoon desirable envelope can facilitate a number of navigation functions of the platoon. For example, the desirable envelope can be taken into account … Obstacle detection and avoidance programs can utilize a desirable envelope in a number of ways. For example, if an obstacle is detected in a particular lane to interfere with some portion of the platoon, the formation can be adjusted to make certain that the desirable envelope is not violated by the obstacle. In the event that an obstacle is dynamic, for example, a vehicle in front of the platoon slowing and indicating a turn outside of the path of the platoon, only vehicles that will have minimum desirable ranges predictably impacted by the dynamic obstacle need to be adjusted. If a column of five vehicles exist in the particular lane, but a prediction is made that only the first two vehicles in the column will be affected by the dynamically changing obstacle, room can be made in the formation for the two vehicles to switch lanes, while the remaining three vehicles in the column can be maintained in their current positions in the formation. Upon the change, the platoon desirable envelope can be reformulated, and reactions can be made if the dynamically changing obstacle fails to follow the predicted behavior.”
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 automated vehicle control system capable of both applying different travel rules to a plurality of vehicles depending on what zone they are in and maintaining clearance envelopes between vehicles and obstacles as taught by Van De Velde, with the teachings of separating zones that determine whether vehicles travel with one another for entertainment outcomes in the context of an amusement ride as taught by Dembinski, the virtual map obstacle information querying which may be applied to the context of a vehicle platoon as taught by Gupta, and the platoon obstacle avoidance methodology of individually moving vehicles on independent trajectories as taught by Mudalige, in order to yield predictable results.
Combining the references would yield the benefits of saving computation resources/energy for moving vehicles upon facing an obstacle by only moving the vehicles that are effected. As Mudalige describes, (Page 37, Column 31, Lines 13-41) “only vehicles that will have minimum desirable ranges predictably impacted by the dynamic obstacle need to be adjusted … Upon the change, the platoon desirable envelope can be reformulated, and reactions can be made if the dynamically changing obstacle fails to follow the predicted behavior,” and further describes, (Page 37, Column 31, Lines 4-7) “In this way, the use of a platoon desirable envelope in the standard V2V message reduces the collision avoidance process complexity and computational load for all V2X equipped vehicles.”
Claim 11 Discloses: (Previously Presented)
“The method of claim 10, further comprising: receiving, by the processor, an updated position of the first vehicle in the operating environment; and updating, by the processor, the position of the first vehicle on the virtual map.”
Van de Velde teaches, (Paragraph [0159], Lines 1-3) “In some preferred embodiment, the VOP 112 is able to create at least one Simultaneous Locating and Mapping (SLAM) map of the environment 106 while navigating along the VAP,” and that, “the present control system 102 may create one or more VAPs, for example, by drawing them onto an existing map of the environment 106,” therefore, (Paragraph [0161], Lines 9-12) “The VOPs 112 are able to enhance their navigational abilities, by combining SLAM (“Simultaneous Locating and Mapping”) methods with RTLS-based localization and navigation methods.”
Claim 12 Discloses: (Previously Presented)
“The method of claim 10, wherein the first vehicle and the second vehicle travel along a same path through the first portion.”
Van de Velde teaches, (Paragraph [0115]) “a specifically delineated area (in 2D or 3D space) within an overall Environment. A Zone is characterized by its boundaries and is typically defined for specific functions, usage, or characteristics within a larger setting … A Zone may have certain Properties and/or Rules associated with it (to e.g., help in establishing control, safety, and efficiency by segmenting larger spaces into manageable, functional areas),” and that, (Paragraph [0145], Lines 11-12) “certain VAPs may overlap or coincide partially or completely with other VAPs,” further wherein, (Paragraph [0148], Lines 20-34) “The traffic rules may include distance restrictions (for example target/min/max distance a VOP 112 should maintain from other VOPs or Objects). The traffic rules may further include “drive center” vs. “drive to the left” vs. “drive to the right” of the VAPs, at certain defined distances. Further, the traffic rules may include right-of-way or other priority rules, for example when multiple VOPs meet at an intersection. All of these traffic rules may be defined (configured) automatically, when drawing, recording, or otherwise defining a new VAP, by applying the default VAP rules, making it very quick and easy to set up and control VOPs 112 in an environment 106.”
Claim 13 Discloses:
“The method of claim 10, further comprising: receiving, by the processor, data associated with an additional obstacle; and updating, by the processor, the virtual map with the additional obstacle.”
Van de Velde teaches, (Paragraph [0014]) “It will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in computer readable medium and so executed by a computing device or processor, whether or not such computing device or processor is explicitly shown.”
Van De Velde additionally teaches, (Paragraph [0256]) “Obstacles are usually unknown by the VOP 112 ahead of time. These are detected and avoided along the way (using for example cameras, ultrasonic sensors, radar, LIDAR, and the like). In an example embodiment, in a “Free-Roam Zone”, the control system 102 finds the shortest safe path along the virtual approved pathways that leads to the destination 416. A discovered route 508 navigates the VOP 112 to the closest VAP needed to reach the destination 416, while avoiding any obstacles along the way.”
Van De Velde additionally teaches, (Paragraph [0064], Lines 4-7) “An Obstacle may be (re)presented as a Virtual Element, by a computer system such as a Control System, on a digital representation of an Environment, such as a Map or Floor Plan or 3D rendering,” and that, (Paragraph [0079], Lines 19-21) “The information is typically relayed to a software platform that processes the data and displays the locations on a map in real time.”
Claim 14 Discloses: (Previously Presented)
“The method of claim 10, further comprising: receiving, by the processor, data associated with a detected environmental feature of the operating environment; and determining, by the processor, the position of the first vehicle based on the detected environmental feature.”
Van de Velde teaches, (Paragraph [0014]) “It will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in computer readable medium and so executed by a computing device or processor, whether or not such computing device or processor is explicitly shown.”
Van De Velde additionally teaches, (Paragraph [0159], Lines 1-3) “In some preferred embodiment, the VOP 112 is able to create at least one Simultaneous Locating and Mapping (SLAM) map of the environment 106,” and that, (Paragraph [0160], Lines 8-15) the VOP 112 maps the environment 106, typically collecting data using one or more LiDAR sensors or possibly using vision cameras or other sensors that are able to map certain aspects and features of the environment 106 in such way that an VOP 112 should be able to recognize certain environmental features at some later time, allowing the VOP to determine its position within the environment 106.”
Claim 15 Discloses: (Original)
“The method of claim 10, wherein the processor is part of a centralized wayside computer.”
Van De Velde teaches, (Paragraph [0019]) “FIG. 1 is a block diagram of an exemplary network architecture 100 capable of controlling or guiding VOPs using Virtual Approved Pathways (VAPs), in accordance with embodiments of the present disclosure. The network architecture 100 may include a control system 102 communicatively coupled to a plurality of objects 110 (also referred as object 110, objects 110, or the like) within an environment 106 via a network 104. The control system 102 may further be connected to one or more user devices 108A-N (collectively referred to as user devices 108A-N) via the network 104 (also referred herein as communication network 104).”
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Van De Velde additionally teaches, (Paragraph [0200], Lines 1-3) “The present invention enables coordinated control of the behavior of VOPs 112 in real time, remotely, and in a centralized fashion.”
Van De Velde additionally teaches, (Paragraph [0124]) “The control system 102 may be a remote server or a local control system … the control system 102 may also reside within the environment 106.”
Claim 16 Discloses: (Currently Amended)
“A method of assigning clearance envelopes within an operating environment, the method comprising: receiving, by a processor and from a sensor of a first vehicle, data associated with an operating environment of the first vehicle;”
Van de Velde teaches, (Paragraph [0159], Lines 1-3) “In some preferred embodiment, the VOP 112 is able to create at least one Simultaneous Locating and Mapping (SLAM) map of the environment 106 while navigating along the VAP,” and that, “the present control system 102 may create one or more VAPs, for example, by drawing them onto an existing map of the environment 106,” therefore, (Paragraph [0161], Lines 9-12) “The VOPs 112 are able to enhance their navigational abilities, by combining SLAM (“Simultaneous Locating and Mapping”) methods with RTLS-based localization and navigation methods.”
Van de Velde additionally teaches, (Paragraph [0160], Lines 8-12) “the VOP 112 maps the environment 106, typically collecting data using one or more LiDAR sensors or possibly using vision cameras or other sensors that are able to map certain aspects and features of the environment 106.”
Van de Velde additionally teaches, (Paragraph [0014]) “It will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in computer readable medium and so executed by a computing device or processor, whether or not such computing device or processor is explicitly shown.”
“identifying, by the processor, an object in the operating environment based on the data;
Van De Velde teaches, (Paragraph [0256]) “Obstacles are usually unknown by the VOP 112 ahead of time. These are detected and avoided along the way (using for example cameras, ultrasonic sensors, radar, LIDAR, and the like). In an example embodiment, in a “Free-Roam Zone”, the control system 102 finds the shortest safe path along the virtual approved pathways that leads to the destination 416. A discovered route 508 navigates the VOP 112 to the closest VAP needed to reach the destination 416, while avoiding any obstacles along the way.”
“… assigning, by the processor, a clearance envelope to the object based on the characteristic of the object;”
Van De Velde teaches, (Paragraph [0129], Lines 7-10) “The VOPs 112 may also be told remotely to increase their distance from certain other Vehicles, People, or any other known objects 110, in order to increase safety.”
Van De Velde additionally teaches, (Paragraph [0240]) “In FIG. 4C, a VAP 421 may have a variance tolerance that allows for an actual path travelled 422-423 to deviate from a path of prescribed destination points 416. A variance tolerance 425 may be based upon a physical distance (for example up to 0.5 meter from a prescribed destination point 416 and/or path) or a percentage of width of a VAP 421 (for example 10% of VAP width). In some embodiments, a variance tolerance of 425 may be adjusted for conditions under which an VOP 112 is operating. For example, a VOP 112 under full load may be allowed a greater variance, a VOP 112 operating in conditions with very little other VOP traffic may be allowed a greater variance tolerance and/or to operate at faster speeds, and a VOP 112 entering an area 424 including persons, and/or sensitive equipment or machines may be limited to very slow speed and very small variance tolerance.”
“… moving the first vehicle and a second vehicle individually through a first portion of the operating environment; moving the first vehicle and the second vehicle together as a group through a second portion of the operating environment;”
Van De Velde does not teach an explicit first portion of the operating environment wherein a first a second vehicle must move individually and second portion of the operating environment wherein the first vehicle and the second vehicle synchronously. However, Van de Velde does teach demarcating travelable zones with particular rules associated with them, that may for example, dictate the acceptable pathing of each vehicle, which may be influenced by whether another vehicle is present in the environment.
Van De Velde teaches, (Paragraph [0115]) “a specifically delineated area (in 2D or 3D space) within an overall Environment. A Zone is characterized by its boundaries and is typically defined for specific functions, usage, or characteristics within a larger setting … A Zone may have certain Properties and/or Rules associated with it (to e.g., help in establishing control, safety, and efficiency by segmenting larger spaces into manageable, functional areas),” wherein, (Paragraph [0157], Lines 21-29) “depending on the circumstances, zones, pathways, stations, and even other VOPs 112, the VOPs 112 may inherit or overrule each other's properties and/or rules. For example, certain zones may have rules that take priority over (“overrule”) certain rules associated with certain pathways, pathway sections, or stations that fall within those zones. For example, all path sections within a certain zone may be off-limits to a certain class of the VOPs 112.” Therefore, certain zones may accept vehicles while limiting and/or rerouting others.
Van De Velde additionally teaches, (Paragraph [0179], Lines 6-14) “the control system 102 is configured to actively launch one or more VOPs 112 to the VAP section and to specific sections within the environment 106 for validating the identified current state, re-determine the plurality of environmental conditions and re-transmit the first set of parameters at real-time. The one or more VOPs 112 that are determined to be available and capable of performing the task, navigate and reach the destination point.” Therefore, VOPs are additionally capable of traveling together as a group through the environment.
Dembinski does explicitly teach a first portion of the operating environment wherein a first vehicle and second vehicle must move individually.
Dembinski is relevant to the Applicant’s disclosure due to its teachings of designating zones for amusement ride vehicles that dictate whether said vehicles travels individually or synchronously as a group.
Dembinski teaches, (Abstract, Lines 1-3) “A ride control system includes a central controller configured to synchronize movements of separate groups of ride vehicles along a path,” wherein, (Page 12, Column 12, Lines 48-57) “For example, each ride vehicle 16 of the virtual train 52 may travel together (e.g., during a first instance 111) along the path 20 until the virtual train 52 reaches the split-path portion 110. Once the virtual train 52 reaches the split-path portion 110, one or more of the ride vehicles 16 may travel along the path 20a while the other ride vehicles 16 travel along the path 20b (e.g., during a second instance 113). Indeed, any suitable number or subset of the ride vehicles 16 may travel along either the path 20a or the path 20b.”
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Dembinski additionally does explicitly teach wherein a second portion of the environment wherein the first vehicle and the second vehicle synchronously.
Dembinski teaches, (Page 13, Column 11, Lines 3-6) “when in the loading area 54 (FIG. 2), the central controller 22 may assign schedules to the ride vehicles 16 such that the ride vehicles 16 travel within a certain virtual train 52.”
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 automated vehicle control system capable of applying different travel rules to a plurality of vehicles depending on what zone they are in as taught by Van De Velde, with the teachings of separating zones that determine whether vehicle travel with one another in the context of an amusement ride as taught by Dembinski, in order to yield predictable results.
Combining the references would yield the benefits of being able to modify the entertainment experience in the context of an amusement park by varying the positioning and/or platooning of vehicles. As Dembinski describes, (Pag 13, Column 12, Lines 66-67 & Page 14, Column 13, Lines 1-2) “After traveling through the split-path portion 110, the ride vehicles 16 may converge or rejoin the ride vehicles 16 in a different order than before the split -path portion 110, as shown,” and that, (Page 13, Column 11, Lines 40-45) “some ride vehicles 16 may have different experiences along the path 20 according to their relative position. For example, the ride vehicles 16 may experience different special effects or travel along different portions of the path 20 based at least on their relative position within the virtual train 52,” and further that, (Page 13, Column 12, Lines 18-23) “In another example, in contrast to trains or longer coupled vehicles that may experience irregularity in globally-applied motion effects (e.g., more intense effects at the ends relative to the middle of the train), the virtual trains 52 may be capable of providing more uniform experiences, if desired, during motion effects.”
“querying, by the processor, a virtual map for a characteristic of the object; and adjusting … a trajectory of the first vehicle to avoid the object based on the clearance envelope.”
Van De Velde and Dembinski do not explicitly teach the preceding limitations. However, Van de Velde does teach the following.
Van de Velde teaches, (Paragraph [0161], Lines 9-12) “The VOPs 112 are able to enhance their navigational abilities, by combining SLAM (“Simultaneous Locating and Mapping”) methods with RTLS-based localization and navigation methods.” Therefore, Van De Velde teaches comparing, by the first vehicle and using a virtual map, a position of the first vehicle to a position of an obstacle.
Van de Velde additionally teaches, (Paragraph [0147], Lines 23-32) “The data collected may be used to determine whether or not a certain trajectory is (for example) feasible, safe, effective, and/or efficient, or anticipated to be (for example) feasible, safe, effective, and/or efficient for the intended activity and/or objective by one or more specific VOPs 112 at a certain current or future time, depending on possibly dynamic circumstances (e.g. actual or expected or predicted congestion or obstacles in certain areas of the environment 106,” wherein for example, (Paragraph [0148], Lines 8-16) “The certain restrictions may include allowing directionality (possibly further restricted based on certain circumstances, e.g. whether a VOP 112 is carrying a Load, or pulling/pushing a Cart, or not), and height restrictions (e.g. certain VOPs 112 fit under certain racks or conveyors, while others VOPs 112 may not or; a VOP 112 may fit and be able to travel under a certain obstacle while empty, but not while carrying a Load),” and that (Paragraph [0146], Lines 1-9) “the VAP may be, in whole or in part, parallel to other VAPs or VAP sections, possibly created by the control system 102, on a temporary basis to help the VOP 112 avoid an obstacle, whereby the distance between the parallel VAPs or VAP sections may be defined and adjusted dynamically by the control system 102. Further, the VAP may be changed dynamically, and possibly just-in-time, by the control system 102, as far as the routes or properties or rules are concerned.”
Therefore, the introduction of a particular obstacle causes the dynamic adjustment of routing per vehicle based upon the applicable dimensions and/or clearance envelope, such as having enough clearance to travel underneath an obstacle, which differs per vehicle. Therefore, the applicable routing adjustment per vehicle may vary.
However, Van de Velde does not explicitly teach querying, by the first vehicle, the virtual map for a characteristic of the obstacle; and adjusting, by the first vehicle and separate from the second vehicle, a trajectory of the first vehicle to avoid the obstacle based on a clearance envelope determined from the characteristic.
Gupta does teach querying, by the first vehicle, the virtual map for a characteristic of the obstacle; and adjusting a trajectory of the first vehicle to avoid the obstacle based on a clearance envelope determined from the characteristic.
Despite being directed to an autonomous vehicle traveling on a highway, Gupta is relevant to the Applicant’s disclosure due to its teaching regarding querying a virtual map.
Gupta teaches, in regards to the traveling autonomous vehicle, (Abstract, Lines 1-4) “Methods, systems, and non-transitory computer-readable media are configured to perform operations comprising determining map data and detection data for an area in an environment,” wherein, (Paragraph [0060]) “In addition, the prediction and planning module 616 can generate a motion plan for the vehicle 800 that navigates the vehicle 600 in relation to the predicted location and movement of other obstacles so that collisions are avoided,” and that in regards to, “conventional approaches, navigation of a vehicle based on use of a map and detection of obstacles poses various technological challenges,” (Paragraph [0025], Lines 22-31) “For example, an autonomous system of a vehicle can navigate a highway that goes under an overpass. The autonomous system of the vehicle may not be configured to detect the height of the overpass. Because the autonomous system of the vehicle is not configured to detect the height of the overpass, the autonomous system relies on information in a map to determine whether the height of the overpass, or the clearance under the overpass, is sufficient for the vehicle to safely navigate under the overpass.”
Gupta additionally teaches, (Paragraph [0027], Lines 23-28) “The autonomous system can provide the detection data captured at the environment, such as the clearance under the overpass, to automatically update the map. The updated map, for example, can be used later by an autonomous system of another vehicle to safely navigate the environment,” and that, (Paragraph [0064], Lines 18-20) “The processed data can be selectively communicated to the fleet, including vehicle 600, to assist in navigation of the fleet as well as the vehicle 600 in particular.”
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 system of Van De Velde which determines feasible trajectories for an autonomous vehicle that may avoid obstacles, such as obstacles which create height concerns, with the conventional approach of querying a virtual map for obstacle characteristic information to determine said clearance as taught by Gupta, in order to yield predictable results.
Combining the references yield the well-known benefits of detection redundancy for identifying obstacles that could cause collision by, for example, providing map data to a vehicle that does not have sensor data as an option. As Gupta teaches, (Paragraph [0025, Lines 26-31) Because the autonomous system of the vehicle is not configured to detect the height of the overpass, the autonomous system relies on information in a map to determine whether the height of the overpass, or the clearance under the overpass, is sufficient for the vehicle to safely navigate under the overpass.”
Combining the references may additionally yield well known benefits in the situation where an autonomous vehicle has multiple means for determining a change in the surroundings by implementing a comparison between a sensed environment and that which is queried from map data. As Gupta describes, (Paragraph [0026], Lines 24-27) “A change in an environment can be detected based on a comparison between information in the map and detection data associated with the environment.”
“and adjusting, separate from the second vehicle and by the first vehicle, a trajectory of the first vehicle”
Vane De Velde, Dembinski, and Gupta do not explicitly teach adjusting, by the first vehicle and separate from the second vehicle, a trajectory of the first vehicle to avoid the obstacle.
Mudalige does explicitly teach adjusting, by the first vehicle and separate from the second vehicle, a trajectory of the first vehicle to avoid the obstacle.
Mudalige is relevant to the Applicant’s disclosure due to its teachings of the state of the art, specifically regarding trajectory behavior for a platoon encountering an obstacle.
Mudalige teaches, (Page 37, Column 31, Lines 13-41) “Use of a platoon desirable envelope can facilitate a number of navigation functions of the platoon. For example, the desirable envelope can be taken into account … Obstacle detection and avoidance programs can utilize a desirable envelope in a number of ways. For example, if an obstacle is detected in a particular lane to interfere with some portion of the platoon, the formation can be adjusted to make certain that the desirable envelope is not violated by the obstacle. In the event that an obstacle is dynamic, for example, a vehicle in front of the platoon slowing and indicating a turn outside of the path of the platoon, only vehicles that will have minimum desirable ranges predictably impacted by the dynamic obstacle need to be adjusted. If a column of five vehicles exist in the particular lane, but a prediction is made that only the first two vehicles in the column will be affected by the dynamically changing obstacle, room can be made in the formation for the two vehicles to switch lanes, while the remaining three vehicles in the column can be maintained in their current positions in the formation. Upon the change, the platoon desirable envelope can be reformulated, and reactions can be made if the dynamically changing obstacle fails to follow the predicted behavior.”
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 automated vehicle control system capable of both applying different travel rules to a plurality of vehicles depending on what zone they are in and maintaining clearance envelopes between vehicles and obstacles as taught by Van De Velde, with the teachings of separating zones that determine whether vehicles travel with one another for entertainment outcomes in the context of an amusement ride as taught by Dembinski, the virtual map obstacle information querying which may be applied to the context of a vehicle platoon as taught by Gupta, and the platoon obstacle avoidance methodology of individually moving vehicles on independent trajectories as taught by Mudalige, in order to yield predictable results.
Combining the references would yield the benefits of saving computation resources/energy for moving vehicles upon facing an obstacle by only moving the vehicles that are effected. As Mudalige describes, (Page 37, Column 31, Lines 13-41) “only vehicles that will have minimum desirable ranges predictably impacted by the dynamic obstacle need to be adjusted … Upon the change, the platoon desirable envelope can be reformulated, and reactions can be made if the dynamically changing obstacle fails to follow the predicted behavior,” and further describes, (Page 37, Column 31, Lines 4-7) “In this way, the use of a platoon desirable envelope in the standard V2V message reduces the collision avoidance process complexity and computational load for all V2X equipped vehicles.”
Claim 19 Discloses: (Original)
“The method of claim 16, further comprising scanning, by the sensor, the operating environment.”
Van de Velde teaches, (Paragraph [0160], Lines 8-12) “the VOP 112 maps the environment 106, typically collecting data using one or more LiDAR sensors or possibly using vision cameras or other sensors that are able to map certain aspects and features of the environment 106.”
Claim 20 Discloses: (Currently Amended)
“The method of claim 16, further comprising determining whether the object is known based on a comparison with [[a]] the virtual map.”
Van De Velde teaches, (Paragraph [0172], Lines 23-28) “Therefore, the control system 102 helps to make the pathway smooth and/or straight and connected, interpreting the preferences of the administrator within the known context of the environment 106 (including for example, the available map or floor plan of the environment 106),” and that, (Paragraph [0229], Lines 7-10) “The VOPs 112 may also be told remotely to increase their distance from certain other Vehicles, People, or any other known objects 110, in order to increase safety.”
Claim 23 Discloses: (Original)
“The method of claim 16, wherein the clearance envelope comprises at least one of a vehicle protection envelope or a rider reach envelope.”
Van De Velde teaches, (Paragraph [0129], Lines 7-10) “The VOPs 112 may also be told remotely to increase their distance from certain other Vehicles, People, or any other known objects 110, in order to increase safety.”
Claim 24 Discloses: (Previously Presented)
“The method of claim 1, further comprising adjusting, by the second vehicle, a trajectory of the second vehicle to avoid the obstacle, wherein the obstacle is within the first portion, and wherein the first vehicle and the second vehicle travel along different paths through the first portion to avoid the obstacle.”
Van De Velde, Dembinski, and Gupta do not explicitly teach the preceding limitations.
However, it would have been obvious to arrive at the preceding limitations in light of Mudalige, wherein multiple vehicles can perform obstacle avoidance.
Mudalige teaches, (Page 37, Column 31, Lines 13-41) “Use of a platoon desirable envelope can facilitate a number of navigation functions of the platoon. For example, the desirable envelope can be taken into account … Obstacle detection and avoidance programs can utilize a desirable envelope in a number of ways. For example, if an obstacle is detected in a particular lane to interfere with some portion of the platoon, the formation can be adjusted to make certain that the desirable envelope is not violated by the obstacle. In the event that an obstacle is dynamic, for example, a vehicle in front of the platoon slowing and indicating a turn outside of the path of the platoon, only vehicles that will have minimum desirable ranges predictably impacted by the dynamic obstacle need to be adjusted. If a column of five vehicles exist in the particular lane, but a prediction is made that only the first two vehicles in the column will be affected by the dynamically changing obstacle, room can be made in the formation for the two vehicles to switch lanes, while the remaining three vehicles in the column can be maintained in their current positions in the formation. Upon the change, the platoon desirable envelope can be reformulated, and reactions can be made if the dynamically changing obstacle fails to follow the predicted behavior.”
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 automated vehicle control system capable of both applying different travel rules to a plurality of vehicles depending on what zone they are in and maintaining clearance envelopes between vehicles and obstacles as taught by Van De Velde, with the teachings of separating zones that determine whether vehicles travel with one another for entertainment outcomes in the context of an amusement ride as taught by Dembinski, the conventional approach of querying a virtual map for obstacle characteristic information to determine obstacle clearance as taught by Gupta, and the platoon obstacle avoidance methodology of individually moving vehicles on independent trajectories as taught by Mudalige, in order to yield predictable results.
Combining the references would yield the benefits of saving computation resources/energy for moving vehicles upon facing an obstacle by only moving the vehicles that are effected. As Mudalige describes, (Page 37, Column 31, Lines 13-41) “only vehicles that will have minimum desirable ranges predictably impacted by the dynamic obstacle need to be adjusted … Upon the change, the platoon desirable envelope can be reformulated, and reactions can be made if the dynamically changing obstacle fails to follow the predicted behavior,” and further describes, (Page 37, Column 31, Lines 4-7) “In this way, the use of a platoon desirable envelope in the standard V2V message reduces the collision avoidance process complexity and computational load for all V2X equipped vehicles.”
Claim 25 Discloses: (Previously Presented)
Van De Velde, Dembinski, and Gupta do not explicitly teach the preceding limitations.
However, it would have been obvious to arrive at the preceding limitations in light of Mudalige, wherein a conventional orientation of a fleet comprises vehicles which travel within different lanes as part of a platoon.
Mudalige teaches, (Page 37, Column 31, Lines 13-41) “Use of a platoon desirable envelope can facilitate a number of navigation functions of the platoon. For example, the desirable envelope can be taken into account … Obstacle detection and avoidance programs can utilize a desirable envelope in a number of ways. For example, if an obstacle is detected in a particular lane to interfere with some portion of the platoon, the formation can be adjusted to make certain that the desirable envelope is not violated by the obstacle. In the event that an obstacle is dynamic, for example, a vehicle in front of the platoon slowing and indicating a turn outside of the path of the platoon, only vehicles that will have minimum desirable ranges predictably impacted by the dynamic obstacle need to be adjusted. If a column of five vehicles exist in the particular lane, but a prediction is made that only the first two vehicles in the column will be affected by the dynamically changing obstacle, room can be made in the formation for the two vehicles to switch lanes, while the remaining three vehicles in the column can be maintained in their current positions in the formation. Upon the change, the platoon desirable envelope can be reformulated, and reactions can be made if the dynamically changing obstacle fails to follow the predicted behavior,” wherein, (Page 23, Column 3, Lines 7-9) “FIG. 27 depicts operation of an exemplary desirable envelope around a platoon of vehicles, in accordance with the present disclosure,” comprising vehicles traveling in different lanes/paths as part of a controlled platoon.
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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 automated vehicle control system capable of both applying different travel rules to a plurality of vehicles depending on what zone they are in and maintaining clearance envelopes between vehicles and obstacles as taught by Van De Velde, with the teachings of separating zones that determine whether vehicles travel with one another for entertainment outcomes in the context of an amusement ride as taught by Dembinski, the conventional approach of querying a virtual map for obstacle characteristic information to determine obstacle clearance as taught by Gupta, and the platoon obstacle avoidance methodology of individually moving vehicles in different lanes as part of a platoon envelope as taught by Mudalige, in order to yield predictable results.
Combining the references would yield the benefits of saving computation resources/energy for moving vehicles upon facing an obstacle by only moving the vehicles that are effected. As Mudalige describes, (Page 37, Column 31, Lines 13-41) “only vehicles that will have minimum desirable ranges predictably impacted by the dynamic obstacle need to be adjusted … Upon the change, the platoon desirable envelope can be reformulated, and reactions can be made if the dynamically changing obstacle fails to follow the predicted behavior,” and further describes, (Page 37, Column 31, Lines 4-7) “In this way, the use of a platoon desirable envelope in the standard V2V message reduces the collision avoidance process complexity and computational load for all V2X equipped vehicles,” as well as, (Page 36, Column 30, Lines 20-24) “By evaluating positions of vehicles within a platoon and applying minimum desirable ranges from all of the current vehicle positions, a desirable envelope can be defined. By controlling the platoon according to a desirable envelope, the platoon can be navigated.”
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Van de Velde in view of Dembinski, further in view of Gupta, further in view of Mudalige, further in view of Alagic et al. (US 11,762,390 B1, hereinafter Alagic)
Claim 17 Discloses: (Currently Amended)
“The method of claim 16, wherein the data comprises a segment point cloud generated by the sensor,”
Van de Velde, Dembinski, and Mudalige do not explicitly teach generating a segment point cloud; however, Van de Velde does teach that, (Paragraph [0160], Lines 8-12) “the VOP 112 maps the environment 106, typically collecting data using one or more LiDAR sensors or possibly using vision cameras or other sensors that are able to map certain aspects and features of the environment 106.”
Gupta does teach generating a segment point cloud.
Gupta teaches, (Paragraph [0031], Lines 32-33) “The 3D reconstructions can include high density point clouds of the area based on LiDAR data.”
“and wherein the method further comprises removing, by the processor, points from the segment point cloud that are known based on [[a]]the virtual map of the operating environment.”
Gupta does not explicitly teach removing, by the processor, points from the segment point cloud that are known based on the virtual map of the operating environment.
However, Gupta does teach, (Paragraph [0033], Lines 43-45) “LiDAR data in the detection data can be compared with a point cloud in the map data to add additional points to the high density point cloud or remove or modify inaccurate points in the high density point cloud.”
Alagic does teach removing detected points that are already present in a virtual map.
Alagic teaches, (Page 15, Column 4, Lines 62-67 & Page 16, Column 5, Lines 1-7) “According to embodiments, the environment interpretation module 110 includes a localization and mapping module 111, an object recognition and tracking module 112, and a moving object trajectory prediction module 113. In an embodiment, the localization and mapping module 111 receives the sensor data and combines the sensor data with historical data associated with the environment, the AGV 101, one or more known objects, etc. … In an embodiment, the localization and mapping module 111 further generate a map of the environment.”
Alagic additionally teaches, (Page 21, Column 15, Lines 44-48) “In an embodiment, the raw point cloud generated in FIG. 7 can be large and difficult to process by the safety management controller without adding significant complexity. In an embodiment, the point cloud is downsampled to remove redundant or noisy 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 automated vehicle environment control system of Van De Velde with the explicit segment point cloud system of Gupta, and the redundant point cloud data removal for data already measured and stored in a map as taught by Alagic, in order to yield predictable results.
Combining the references would yield the benefits of more easily managing a smaller dataset by only measuring new potential obstacle detections in a segment point cloud. As Alagic describes, (Page 21, Column 15, Lines 44-48) “the raw point cloud generated in FIG. 7 can be large and difficult to process by the safety management controller without adding significant complexity. In an embodiment, the point cloud is downsampled to remove redundant or noisy data.”
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Van De Velde in view of , Dembinski, further in view of Gupta, further in view of Mudalige, further in view of Alagic, further in view of Klein et al. (US 10,215,858 B1, hereinafter Klein)
Claim 18 Discloses: (Previously Presented)
“The method of claim 17, wherein the identifying the object comprises: converting, by the processor, at least some of the remaining points of the segment point cloud to a shape; and analyzing the shape based on an object database to associate the shape with an expected object.”
Van De Velde, Dembinski, Gupta, Mudalige, and Alagic do not teach analyzing the shape based on an object database to associate the shape with an expected object.
Klein does teach converting at least some of the remaining points of the segment point cloud to a shape; and analyzing the shape based on an object database to associate the shape with an expected object, in the context of, (Page 13, Column 7, Lines 6-8) “a robotic device can measure aspects of the environment using sensors that capture data as the robotic device travels.”
Klein teaches, (Page 11, Column 4, Lines 22-35) “the computing system may further determine whether detected clusters of data points that appear to form and maintain rigid shape configurations in point cloud representations correspond to physical objects in the environment. For example, a computing system may use a database that contains information about various objects to assist in determining whether a detected rigid shape likely corresponds to an object in the environment. Particularly, the database may provide the computing system with access to information that enables comparisons between various aspects of the detected rigid shape with previously identified objects, including comparing information detailing shapes and sizes of objects that may be potentially detected within the environment.”
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filling date to combine the disclosure of Van De Velde, Dembinski, Gupta, Mudalige, and Alagic with a point cloud shape comparison to an object database as taught by Klein, in order to yield predictable results.
Combining the references would yield the well-known benefits of more accurate object classification detection by comparing data to that previously stored in a database. As Klein describes, (Page 11, Column 3, Lines 42-44) “To reduce inaccurate association of data points, a computing system may be configured to perform one or more rigid body object detection processes described herein.”
Claims 21-22 are rejected under 35 U.S.C. 103 as being unpatentable over Van De Velde in view of Dembinski, further in view of Gupta, further in view of Mudalige, further in view of Klein.
Claim 21 Discloses: (Currently Amended)
“The method of claim 16, wherein the identifying comprises analyzing the object based on [[the]] an object recognition process to associate the object with an expected object.”
Van De Velde does not explicitly teach an object recognition algorithm to associate an object with an expected object. However Van De Velde does teach, (Paragraph [0046], Lines 1-6) “a computer system that stores and/or accesses certain data and that runs certain algorithms to interpret such data, including but not limited to data provided by a VOP, and possibly provided by other VOPs operating in the same Environment, and/or data captured through certain Sensors present in the Environment.”
Dembinski, Gupta and Mudalige do not teach the preceding limitations.
Klein does explicitly teach using an object recognition algorithm in the context of, (Page 13, Column 7, Lines 6-8) “a robotic device can measure aspects of the environment using sensors that capture data as the robotic device travels.”
Klein teaches, (Page 14, Column 10, Lines 33-35) “computing system 100 may utilize an algorithm that searches for rigid shapes, such as cubes, rectangular shapes, or other rigid shapes that are evident in objects,” and that, (Page 17, Column 15, Lines 57-64) “computing system 100 may use additional information received from a computing device and/or other sensors operating in environment 200 to perform object recognition of the table and chair. Additionally, computing system 100 may also update a database that includes information regarding objects in environment 200 based on any information determined after performing the rigid shape object detection process.”
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filling date to combine the disclosure of Van De Velde with an explicit object recognition algorithm such as the one taught by Klein, in order to yield predictable results.
Combining the references would yield the well-known benefits of more accurate object recognition by using an algorithm to compare data to that previously stored in a database. As Klein describes, (Page 11, Column 3, Lines 42-44) “To reduce inaccurate association of data points, a computing system may be configured to perform one or more rigid body object detection processes described herein.”
Claim 22 Discloses: (Currently Amended)
“The method of claim 21, wherein the expected object is a second vehicle.”
Van De Velde teaches, (Paragraph [0129], Lines 7-10) “The VOPs 112 may also be told remotely to increase their distance from certain other Vehicles, People, or any other known objects 110, in order to increase safety.”
RELEVANT, BUT NOT CITED PRIOR ART
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Yamada (US 2024/0231381 A1) teaches, (Paragraph [0041]) “In order to enable display of the information presentation example, the exclusion management unit 502 functions more specifically as follows. First, the exclusion management unit 502 receives a prediction motion 702 for the manned moving bodies 1b and 1c from the moving body motion prediction unit 501. In the display example of FIG. 5, the prediction motion 702 is at the illustrated position for each moving body 1, and is configured by the average value and the standard deviation of the distribution obtained from the probability density distribution indicating the prediction position after 0 second, 1.5 seconds, and 3 seconds. FIGS. 5 to 7 illustrate the prediction motion 702 by a circle having the average value as the center and the standard deviation as the radius. Note that the prediction position after 0 seconds is the estimation position at that time.”
Buerkle et al., (US 12,442,896 B2) teaches, (Page 11, Column 7, Lines 27-31) “As shown in FIG. 2, one component of hierarchical monitoring system 200 may be a model-based probability filter 232, which may use model knowledge to determine the probability for each point in the point of belonging to a relevant object,” and that, (Page 10, Column 5, Lines 5-7) “Consequently, it may be possible to define a safety relevant zone around the ego vehicle at distance which encompasses the safety-relevant objects.”
Conclusion
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/ALEXANDER V GENTILE/ Examiner, Art Unit 3664
/TYLER D PAIGE/ Primary Examiner, Art Unit 3664
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