DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This is a Non-Final rejection on the merits of this application. Claims 1-20 are currently pending, as discussed below.
Examiner Notes that the fundamentals of the rejections are based on the broadest reasonable interpretation of the claim language. Applicant is kindly invited to consider the reference as a whole. References are to be interpreted as by one of ordinary skill in the art rather than as by a novice. See MPEP 2141, Therefore, the relevant inquiry when interpreting a reference is not what the reference expressly discloses on its face but what the reference would teach or suggest to one of ordinary skill in the art.
Information Disclosure Statement
The information disclosure statement (IDS) filed on 07/30/2025 is being considered by the examiner.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding Claim 1 (similarly claims 10 and 19), the recited limitation “the global path comprising at least one node having a node probability that a physical location associated with the at least one node lacks a physical object, and at least one edge having an edge probability that the at least one edge is traversable, the edge probability being determined based on a time, indicated in the dense map or the sparse map, when a physical location associated with the one edge was visited” is indefinite for at least the following reason:
(1) what is a node probability (e.g., is the probability stored in the node? Is the probability associated with the at lest one node represented that physical location of the node lacks obstacle? Or something else?
(2) the limitation “when a physical location associated with the one edge was visited” is unclear and confusing to the Examiner: (i) what does/does not constitute as “a physical location associated with the one edge”, for example, midpoint of the edge, the endpoint of the edge, the full edge, or something else? (ii) what constitutes as “visited”, for example, physically traversed, observed by a sensor far away?
(3) the recited limitation of “a physical location” in Lines 12-13 in indefinite because it is unclear for instance if applicant intends to introduce a new physical location which is different than the one already claimed in Line 9 since the phrase “a physical location” is used again which implies that a new physical location different from the one in Line 9 is being introduced to the claim.
Accordingly, these claim limitations renders the claim to be indefinite.
Claim 19 recites the limitation "the unmanned aerial vehicle" in Line 10. There is insufficient antecedent basis for this limitation in the claim.
The dependent claims that dependent upon independent claims are also rejected under 112 second paragraph by the fact that they are dependent upon the rejected independent claims.
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.
Claim(s) 1-7, 10-16 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Yang et al. (US 2022/0113423 A1 hereinafter Yang) in view of Mohan et al. (US 2022/0026890 A1 hereinafter Mohan).
Regarding Claim 1 (similarly claims 10 and 19), Yang teaches An unmanned aerial vehicle (see at least Fig. 1) comprising:
a flight control subsystem (see at least Fig. 1-3 [0035]: Flight controller 114); and
an electromechanical subsystem coupled with the flight control subsystem and configured to fly the unmanned aerial vehicle as directed by the flight control subsystem; (see at least Fig. 1-3 [0035]: The flight controller 114 can send movement commands to the movement mechanism 116 (e.g., rotors, propellers, blades, engines, motors, wheels, axles, etc.) to control movement of the movable object.)
wherein the flight control subsystem (see at least Fig. 1-3 [0035]: The flight controller 114) is configured to:
generate dense maps during flight, wherein the dense maps represent locations of physical objects in a three-dimensional space; (see at least Fig. 1-3 [0065-0081]: The UAV scanning sensor can receive data from scanning sensor and positioning sensor to produce mapping data in a point cloud data which may be a 3D representation of the target environment. The geo-referenced point cloud data may be provided to map generator which may include a dense map generator and a sparse map generator. The dense map generator can produce a high-density map to be used with various mapping, planning, analysis, or other tools to be rendered on the mobile device through the visualization application.)
generate a global graph based on the dense maps and a sparse map (see at least Fig. 1-3 [0065-0100]: The generated point cloud data is a three-dimensional representation of a target object or a target environment. The map generator may include a dense map generator and sparse map generator. Dense map generator and sparse map generator may produce a high-density map and a low-density map separately from the point cloud data received. Each map generator may generate the output map using the same process but may vary the size of the voxels to produce high-density or low-density maps. In some embodiments, the low-density map can be used by a client device 110 or a mobile device to provide visualization of the mapping data. The high-density map can be output as a LIDAR Data Exchange File (LAS) or other file type (such as PLY file) to be used with various mapping, planning, analysis, or other tools or to be rendered on the mobile device through the visualization application.)
receive a trigger to move the unmanned aerial vehicle to a position in the three- dimensional space; (see at least [0149]: As battery is one of the most restricted elements in a movable object, the application may seriously consider the status of battery not only for the safety of the movable object but also for making sure that the movable object can finish the designated tasks. For example, the battery class 1803 can be configured such that if the battery level is low, the movable object can terminate the tasks and go home outright.)
It may be alleged that Yang does not explicitly teach the global graph comprising at least one node having a node probability that a physical location associated with the at least one node lacks a physical object, and at least one edge having an edge probability that the at least one edge is traversable, the edge probability being determined based on a time, indicated in the dense maps or the sparse map, when a physical location associated with the at least one edge was visited;
determine, using the global graph, a path to the position that avoids the physical objects in response to the trigger; and
navigate the unmanned aerial vehicle to the position using the determined path.
Mohan is directed to system and method for controlling deployment and operation of one or more autonomous navigation system, Mohan teaches the global graph comprising at least one node having a node probability that a physical location associated with the at least one node lacks a physical object, and at least one edge having an edge probability that the at least one edge is traversable, the edge probability being determined based on a time, indicated in the dense maps or the sparse map, when a physical location associated with the at least one edge was visited; (see at least Fig. 3-6 [0037-0052]: The map 90 includes nodes and communities that may be adjusted and updated as the survey system surveys the environment (i.e., updated after physical location associated with edge was visited by robot(s)). The map 90 is a graph including a plurality of nodes 92 representing various locations within the environment 5 and a plurality of edges 94 connecting the nodes 92. The map includes traversability scores disposed proximate to the edges in a numeric range (e.g., 0 to 1 ), a categorical description/textual string, among other metrics representing a traversability of a given robot between a given set of nodes 92. The central controller 70 is configured to select one of the robots 20 , 30 , 40 to survey a given area of the environment 5 based on one or more traversability scores of a corresponding node 92 and/or paths representing the corresponding edges 94.)
determine, using the global graph, a path to the position that avoids the physical objects in response to the trigger; and navigate the unmanned aerial vehicle to the position using the determined path. (see at least Fig. 3-6 [0037-0052]: The central controller 70 is configured to select one of the robots 20 , 30 , 40 to survey a given area of the environment 5 (i.e. trigger) based on one or more traversability scores of a corresponding node 92 and/or paths representing the corresponding edges 94 (i.e. determined path).)
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Yang’s system and method for generating map data for an environment to incorporate the technique of assigning traversability scores to nodes and edges connecting the nodes in an environment based on survey results and planning traversal paths based on the traversabilities scores of the environment as taught by Mohan with reasonable expectation of success to ensure safer path planning so the robot can avoid routes that are unsafe in order to improve mission success rate.
Regarding Claim 2 (similarly claims 11 and 20), the combination of Yang in with of Mohan teaches The unmanned aerial vehicle of claim 1,
Yang further teaches wherein the dense maps represent a flight path. (see at least Fig. 1-3 [0042-0043]: once a mapping mission is complete, sensor data may be obtained from the payload 124 and provided to computing device 126 for post-processing.)
Regarding Claim 3 (similarly claim 12), the combination of Yang in with of Mohan teaches The unmanned aerial vehicle of claim 1,
It may be alleged that Yang does not explicitly teach wherein the at least one node is associated with a node traversal time when a physical location represented by the at least one node was traversed, wherein the node probability is determined based on the node traversal time.
Mohan is directed to system and method for controlling deployment and operation of one or more autonomous navigation system, Mohan teaches wherein the at least one node is associated with a node traversal time when a physical location represented by the at least one node was traversed, wherein the node probability is determined based on the node traversal time. (see at least Fig. 3-6 [0037-0052]: The map 90 includes nodes and communities that may be adjusted and updated as the survey system surveys the environment (i.e., updated after physical location associated with edge was visited by robot(s)). The map 90 is a graph including a plurality of nodes 92 representing various locations within the environment 5 and a plurality of edges 94 connecting the nodes 92. The map includes traversability scores disposed proximate to the edges in a numeric range (e.g., 0 to 1 ), a categorical description/textual string, among other metrics representing a traversability of a given robot between a given set of nodes 92. The central controller 70 is configured to select one of the robots 20 , 30 , 40 to survey a given area of the environment 5 based on one or more traversability scores of a corresponding node 92 and/or paths representing the corresponding edges 94.)
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Yang’s system and method for generating map data for an environment to incorporate the technique of assigning traversability scores to nodes and edges connecting the nodes in an environment based on survey results and planning traversal paths based on the traversabilities scores of the environment as taught by Mohan with reasonable expectation of success to ensure safer path planning so the robot can avoid routes that are unsafe in order to improve mission success rate.
Regarding Claim 4 (similarly claim 13), the combination of Yang in with of Mohan teaches The unmanned aerial vehicle of claim 1, wherein the flight control subsystem is further configured to:
Yang further teaches generate the sparse map, the sparse map comprising sparse map nodes representing sparse map locations in the three-dimensional space (see at least Fig. 1-3 [0065-0100]: The generated point cloud data is a 3D representation of a target object or a target environment. The map generator may include a dense map generator and sparse map generator. Dense map generator and sparse map generator may produce a high-density map and a low-density map separately from the point cloud data received. Each map generator may generate the output map using the same process but may vary the size of the voxels to produce high-density or low-density maps. In some embodiments, the low-density map can be used by a client device 110 or a mobile device to provide visualization of the mapping data. The high-density map can be output as a LIDAR Data Exchange File (LAS) or other file type (such as PLY file) to be used with various mapping, planning, analysis, or other tools or to be rendered on the mobile device through the visualization application.) and
It may be alleged that Yang does not explicitly teach sparse map edges representing connections between the sparse map locations.
Mohan is directed to system and method for controlling deployment and operation of one or more autonomous navigation system, Mohan teaches the sparse map comprising sparse map nodes representing sparse map locations in the three-dimensional space and sparse map edges representing connections between the sparse map locations. (see at least Fig. 3-5)
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Yang’s system and method for generating map data for an environment to incorporate the technique of generating a map representation of the 3D environment with nodes and edges connecting nodes as taught by Mohan with reasonable expectation of success to ensure safer path planning so the robot can avoid routes that are unsafe in order to improve mission success rate.
Regarding Claim 5 (similarly claim 14), the combination of Yang in with of Mohan teaches The unmanned aerial vehicle of claim 4,
It may be alleged that Yang does not explicitly teach wherein a sparse map edge between two sparse map nodes represents whether a sparse map path exists between the locations associated with the two sparse map nodes.
Mohan is directed to system and method for controlling deployment and operation of one or more autonomous navigation system, Mohan teaches wherein a sparse map edge between two sparse map nodes represents whether a sparse map path exists between the locations associated with the two sparse map nodes. (see at least Fig. 3-5)
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Yang’s system and method for generating map data for an environment to incorporate the technique of generating a map representation of the 3D environment with nodes and edges connecting nodes as taught by Mohan with reasonable expectation of success to ensure safer path planning so the robot can avoid routes that are unsafe in order to improve mission success rate.
Regarding Claim 6 (similarly claim 15), the combination of Yang in with of Mohan teaches The unmanned aerial vehicle of claim 1, wherein determining the path to the position comprises:
Yang further teaches determining the path using the dense maps. (see at least Fig. 1-3 [0065-0081]: The UAV scanning sensor can receive data from scanning sensor and positioning sensor to produce mapping data in a point cloud data which may be a 3D representation of the target environment. The geo-referenced point cloud data may be provided to map generator which may include a dense map generator and a sparse map generator. The dense map generator can produce a high-density map to be used with various mapping, planning, analysis, or other tools to be rendered on the mobile device through the visualization application.)
Regarding Claim 7 (similarly claim 16), the combination of Yang in with of Mohan teaches The unmanned aerial vehicle of claim 1,
Yang further teaches wherein the trigger comprises a request to return to a dock of the unmanned aerial vehicle, wherein the position corresponds to the dock. (see at least [0149]: As battery is one of the most restricted elements in a movable object, the application may seriously consider the status of battery not only for the safety of the movable object but also for making sure that the movable object can finish the designated tasks. For example, the battery class 1803 can be configured such that if the battery level is low, the movable object can terminate the tasks and go home outright.)
Claim(s) 8-9 and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Yang in view of Mohan and Liu et al. (US 2016/0070265 A1 hereinafter Liu).
Regarding Claim 8 (similarly claim 17), the combination of Yang in with of Mohan teaches The unmanned aerial vehicle of claim 1,
Yang further teaches wherein the flight control subsystem comprises processing circuitry and a memory (see at least Fig. 1-3), wherein the global graph is represented, in the memory(see at least Fig. 1-3), as a graph with the nodes and edges, wherein an edge between two nodes indicates whether the unmanned aerial vehicle can travel, without hitting physical objects, in an unobstructed straight line between the locations represented by the two nodes.
It may be alleged that the combination of Yang in view of Mohan doesn’t explicitly teach wherein the global graph is represented, in the memory, as a graph with the nodes and edges, wherein an edge between two nodes indicates whether the unmanned aerial vehicle can travel, without hitting physical objects, in an unobstructed straight line between the locations represented by the two nodes.
Liu is directed to UAV multi-sensor environmental mapping system and method, Liu teaches wherein the global graph is represented, in the memory, as a graph with the nodes and edges, wherein an edge between two nodes indicates whether the unmanned aerial vehicle can travel, without hitting physical objects, in an unobstructed straight line between the locations represented by the two nodes. (see at least [0088-0092]: UAV sensor data can be used to generate a representation of the environment, environmental map, that represents portions of the environment within the immediate proximity of the UAV (local map), or may also represent portions that are relatively far from the UAV (global map). The map can provide information indicating which portions of the environment are obstructed (e.g., cannot be traversed by the UAV) and which portions are unobstructed (e.g., can be traversed by the UAV). A topological environmental map can be provided as a graph having vertices representing locations and edges representing paths between the locations.)
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Yang and Mohan to incorporate the technique of representing a graph with nodes and edges wherein an edge between two nodes indicates whether the unmanned aerial vehicle can travel, without hitting physical objects, in an unobstructed straight line between the locations represented by the two nodes as taught by Liu with reasonable expectation of success that uses various sensor data to generate environmental map to improve UAV functionality in diverse environment types and operating conditions (Liu [0004]).
Regarding Claim 9 (similarly claim 18), the combination of Yang in view of Mohan and Liu teaches The unmanned aerial vehicle of claim 8,
It may be alleged that Yang and Liu does not explicitly teach wherein a value of the edge between the two nodes that indicates whether the unmanned aerial vehicle can travel in the unobstructed straight line between the two nodes is determined based on one or more of the dense maps.
Mohan is directed to system and method for controlling deployment and operation of one or more autonomous navigation system, Mohan teaches wherein a value of the edge between the two nodes that indicates whether the unmanned aerial vehicle can travel in the unobstructed straight line between the two nodes is determined based on one or more of the dense maps. (see at least Fig. 3-5 [0037-0052]: The map 90 includes traversability scores disposed proximate to the edges 94 . In one form, the traversability score is a numeric range (e.g., 0 to 1 ), a categorical description/textual string, among other metrics representing a traversability of a given robot (e.g., the central robot 20 ) between a given set of nodes 92 . As an example and as shown in FIG. 3, a higher traversability score corresponds to increased traversability between a set of nodes 92 , and a lower score corresponds to inhibited traversability between a set of nodes 92 . Furthermore and as shown in FIG. 3, a pair of traversability scores are provided proximate to each edge 94 , and each traversability score corresponds to one of the robots of the survey system 10.)
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Yang and Liu to incorporate the technique of indicating traversability of an edge connecting two nodes with numerical value as taught by Mohan with reasonable expectation of success to ensure safer path planning so the robot can avoid routes that are unsafe in order to improve mission success rate.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANA F ARTIMEZ whose telephone number is (571)272-3410. The examiner can normally be reached M-F: 9:00 am-3:30 pm EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Faris S. Almatrahi can be reached at (313) 446-4821. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DANA F ARTIMEZ/Examiner, Art Unit 3667
/FARIS S ALMATRAHI/Supervisory Patent Examiner, Art Unit 3667
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