DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1-20 are pending.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 04/15/2025 and 07/09/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Claim Objections
Claims 4 and 7 are objected to because of the following informalities:
Claim 4 line 2: “robotic arms at least two of which” should be changed to read “robotic arms, wherein at least two of which”.
Claim 7 lines 1-2: “on or more of the following” should be changed to read “one or more of the following”.
Appropriate correction is required.
Claim Rejections - 35 USC § 103
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.
Claims 1-3, 7-13, and 16-20 are rejected under 35 U.S.C. 103 as being unpatentable over Go et al. (US 2022/0350582 A1), in view of Matsuoka et al. (US 2022/0135346 A1).
Regarding claim 1, Go teaches:
A robotic system (Fig. 1; [0038] “an example network environment 100”), comprising:
a memory (Fig. 8; [0099] “memory 804”) configured to store configuration information ([0102] “ Memory 804 can include software instructions for the containerized software packages 106′, 108’”) for each of a plurality of robotic applications ([0048] “a robotic task required may include multiple sub-tasks where each sub-task can be handled by a specific containerized software package.”); and
a processor ([0099] “AMR 800 includes a processor 802”) coupled to the memory ([0101] “Memory 804 is typically provided in AMR 800 for access by the processor 802”) and configured to:
receive an indication ([0072] “where at least one robotic task is identified for an associated AMR.”) to perform tasks ([0072] “a plurality of sub-tasks ... processing sensor data, processing visual/camera data, processing navigation data, processing obstacle avoidance data, and other processing tasks”) associated with a selected one of the plurality of robotic applications ([0072] discloses processing tasks as an example of a robotic application);
use the stored configuration information to determine one or both of a required software configuration ... associated with the selected robotic application ([0048] “For example, for a search and report task, an AMR can re-use two containerized software packages, (e.g., one handles object detection from a vision sensor, and, one handles the exploring and searching motion); [0051] “the server 102 can deploy containerized software installation packages (e.g., 106 and 108 ) thereon such that the packages may be executed. Furthermore, the server 102 may direct installation and deployment of containerized software installation packages onto any AMR, e.g., AMRs 130 and 140 . For example, the containerized software installation package 106 may be retrieved from the data store 116 and deployed at the server 102 and the AMR 130 (illustrated as package 106 ′). Additionally, the containerized software installation package 108 may be retrieved from the data store 116 and deployed at the server 102 and the AMR 140 (illustrated as package 108’).”);
update a current software configuration ... of the robotic system as needed to match the required software configuration ... ([0048] “For example, for a search and report task, an AMR can re-use two containerized software packages, (e.g., one handles object detection from a vision sensor, and, one handles the exploring and searching motion); [0051] “the server 102 can deploy containerized software installation packages (e.g., 106 and 108 ) thereon such that the packages may be executed. Furthermore, the server 102 may direct installation and deployment of containerized software installation packages onto any AMR, e.g., AMRs 130 and 140. For example, the containerized software installation package 106 may be retrieved from the data store 116 and deployed at the server 102 and the AMR 130 (illustrated as package 106 ′). Additionally, the containerized software installation package 108 may be retrieved from the data store 116 and deployed at the server 102 and the AMR 140 (illustrated as package 108’).”; [0094] “At block 704 , the containerized software package is deployed at the AMR. For example, the AMR may install, initialize, and execute all or some of the containerized software package. Block 704 is followed by block 706.”); and
use the updated software configuration ... to is autonomously perform tasks associated with the selected robotic application ([0057] “ each AMR may include an operating system 132, 142, a navigation system 134, 144 , and one or more containerized software installation packages 106′, 108′, as described above. Generally, the operating system 132, 142 may be an operating system including all suitable software components to enable initialization and use of the AMR. Additionally, the navigation system 134, 144 may be a software system configured to aid and direct the AMR to navigate a physical environment through obstacle avoidance, mapping, route planning, sensor data, and other aspects.”; [0097] “the robotic tasks completed by the AMR, utilizing the results received from the server 102.”).
Go does not specifically teach the processor is configured to use the stored configuration information to determine a required hardware configuration associated with the selected robotic application, update a current hardware configuration of the robotic system as needed to match the required hardware configuration, and use the updated hardware configuration to is autonomously perform tasks associated with the selected robotic application.
However, in the same field of endeavor, Matsuoka teaches:
a processor is configured to:
use the stored configuration information to determine a required hardware configuration associated with the selected robotic application ([0056] “When the derivation is successful for the existing tool, the corresponding object and the plan can be implemented next. When none of the remaining target objects are appropriate for the currently connected tool, the robotic system 100 can plan for implementing the tool change operation at the end of the ongoing or preceding implementation of the plan. In alternative embodiments, the robotic system 100 can derive and evaluate feasibility and costs of all available tools for each targeted object.”; [0063] “The flat-posed objects 502 can correspond to the targeted objects having an orientation (e.g., a bottom surface of the object) parallel to a bottom surface of the start bin 322 . Accordingly, the standard grasp scenario 500 can correspond to the standard-fixed gripping tool 440.”; [0064] “he angled grasp scenario 510 can be for gripping angled object 512 . The angled object 512 can include objects leaning or resting on uneven contact points (e.g., resting along a non-horizontal plane) and/or objects having non-parallel opposing surfaces. In some embodiments, the angled object 512 can correspond to objects with poses having one or more surfaces oriented along angled directions/planes relative to horizontal/vertical reference directions. Accordingly, the angled grasp scenario 510 can correspond to the fixed-angle gripping tool 450.”),
update a current hardware configuration of the robotic system as needed to match the required hardware configuration ([0056] “During implementation of the first plan, the system manager 302 can interact with the planner 304 to plan for a second object. When the derivation fails, the system manager 302 can select and interact to plan for different objects in an iterative manner in parallel to implementation of the preceding plan. When the derivation is successful for the existing tool, the corresponding object and the plan can be implemented next. When none of the remaining target objects are appropriate for the currently connected too, the robotic system 100 can plan for implementing the tool change operation at the end of the ongoing or preceding implementation of the plan. In alternative embodiments, the robotic system 100 can derive and evaluate feasibility and costs of all available tools for each targeted object.”), and
use the updated hardware configuration to is autonomously perform tasks associated with the selected robotic application ([0056] “During implementation of the first plan, the system manager 302 can interact with the planner 304 to plan for a second object. When the derivation fails, the system manager 302 can select and interact to plan for different objects in an iterative manner in parallel to implementation of the preceding plan. When the derivation is successful for the existing tool, the corresponding object and the plan can be implemented next. When none of the remaining target objects are appropriate for the currently connected too, the robotic system 100 can plan for implementing the tool change operation at the end of the ongoing or preceding implementation of the plan. In alternative embodiments, the robotic system 100 can derive and evaluate feasibility and costs of all available tools for each targeted object.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Go to use the stored configuration information to determine a required hardware configuration associated with the selected robotic application, update a current hardware configuration of the robotic system as needed to match the required hardware configuration, and use the updated hardware configuration to is autonomously perform tasks associated with the selected robotic application, as taught by Matsuoka. Such modification utilizes a set of tools, e.g. specialized end-effectors, to perform different tasks using the same robot and/or improves the performance of a given task, as stated by Matsuoka in [0050].
Regarding claim 2, Go further teaches:
wherein the robotic system comprises a mobile logistics robot ([0035]-[0036] disclose autonomous mobile robot (AMR)).
Regarding claim 3, Go further teaches:
wherein the mobile logistics robot (Fig. 8B) comprises a mobile chassis (Fig. 8B; [0105] “main body 830”) and one or more robotic arms mounted on the mobile chassis ([0046] “manipulation (e.g., using a tool, arm, sprayer, lamp, or other component) of portions of the AMR”; [0106] “although other motion devices such as: ... end-of-arm tooling ...”).
Regarding claim 7, Go further teaches:
wherein required software configuration includes combinations and sequences of primitives to achieve an objective of the selected robotic application ([0045] “ a containerized software package includes, at least, a device driver component configured to allow control over one or more physical components of the AMR, a sensor control component configured to allow reading data provided by one or more sensors of the AMR, and a maneuvering component configured to perform physical maneuvering of the AMR.”); and learned or configured techniques to perform a task or subtask associated with the selected robotic application ([0048] “an AMR can re-use two containerized software packages, (e.g., one handles object detection from a vision sensor, and, one handles the exploring and searching motion)”).
Regarding claim 8, Go does not specifically teach wherein the selected robotic application comprises one or more of the following: truck or container loading, truck or container unloading; truck or container unloading to pallets; palletization; depalletization; sortation; singulation; and kitting.
However, Matsuoka teaches:
wherein the selected robotic application comprises: truck or container loading, truck or container unloading ([0025] “the unloading unit 102 (e.g., a devanning robot) can be configured to transfer the target object 112 from a location in a carrier (e.g., a truck) to a location on a conveyor belt.”); palletization ([0025] “the task can include manipulation (e.g., moving and/or reorienting) of a target object 112 (e.g., one of the packages, boxes, cases, cages, pallets, etc., corresponding to the executing task)”); depalletization ([0026] “a depalletizing unit for transferring the objects from cage carts or pallets onto conveyors or other pallets”); sortation ([0026] “ a sorting unit for grouping objects according to one or more characteristics thereof”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Go, in view of Matsuoka, to include truck or container unloading, truck or container unloading to pallets, palletization, depalletization, and sortation, as taught by Matsuoka, to allow the robot to perform tasks without much human involvements.
Regarding claim 9, Go further teaches
wherein the stored configuration information comprises one or more libraries ([0044] “containerized software packages refer to software applications that are isolated from one another and bundle their own executable code, software libraries, and configuration files.”).
Regarding claim 10, Go further teaches:
one or more cameras or other sensors ([0045] “one or more sensors of the AMR”) and wherein the processor is further configured to use image or other sensor data generated by the one or more cameras or other sensors to autonomously perform tasks associated with the selected robotic application ([0057] “In some implementations, each AMR may include an operating system 132, 142 , a navigation system 134, 144 , and one or more containerized software installation packages 106′, 108′, as described above. Generally, the operating system 132, 142 may be an operating system including all suitable software components to enable initialization and use of the AMR. Additionally, the navigation system 134, 144 may be a software system configured to aid and direct the AMR to navigate a physical environment through obstacle avoidance, mapping, route planning, sensor data, and other aspects. Therefore, each AMR is “autonomous” and can navigate physical environments to arrive and one or more destinations to perform one or more robotic tasks.”; [0074] “ At block 406, the AMR may begin to perform the robotic task. For example, the AMR may retrieve a photo of a valve, read a remote sensor, activate a near-field communication device or a proximity sensor, and/or any other suitable action.”).
Regarding claim 11, Go further teaches one or more cameras or other sensors ([0045] “one or more sensors of the AMR”). Go does not specifically teach wherein the processor is further configured to use image or other sensor data generated by the one or more cameras or other sensors to update its hardware configuration.
However, Matsuoka teaches:
wherein the processor is further configured to use image or other sensor data generated by the one or more cameras or other sensors to update its hardware configuration ([0066] “ In some embodiments, the robotic system 100 can select the fixed-angle gripping tool 450 based on a surface pose 514 for the angled object 512 . For example, the robotic system 100 can process one or more images (e.g., top view images) of the start bin 322 and/or the angled object 512 therein as captured by the imaging devices 222 of FIG. 2. The robotic system 100 can identify the edges depicted in the images based on an edge detection mechanism (e.g., Sobel filter). The robotic system 100 can identify each continuous surface depicted in the images based on determining connections and/or relative orientations between a set of edges and/or recognizing shapes, colors, and/or designs located between the edges. The robotic system 100 can map the surfaces to three-dimensional images (e.g., depth maps) and calculate one or more slopes for each surface using the depth measures. Using the calculated slope(s), the robotic system 100 can derive the surface pose 514 of each surface.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Go, in view of Matsuoka, to use image or other sensor data generated by the one or more cameras or other sensors to update its hardware configuration, as taught by Matsuoka, in order to select a suitable end effector/hardware configuration to perform the assigned task.
Regarding claim 12, Go further teaches:
wherein the indication comprises a first indication (Fig. 5; [0072] “ where at least one robotic task is identified for an associated AMR. The at least one robotic task may include a plurality of sub-tasks, such as processing tasks.”; [0081] “example robotic task 502”) and the processor is further configured to receive a second indication to perform tasks associated with a different one of the plurality of robotic applications (Fig. 5; [0081] “processing task dependencies 504 , 506 , and 508”).
Regarding claim 13, Go further teaches:
a communication interface and wherein the processor is included in a first robot (Fig. 1; [0038] “a first AMR A 130”) comprising the robotic system (Fig. 1) and the processor is further configured to send and receive communications via the communication interface to coordinate work with one or more other robots (Fig. 1; [0038] “a second AMR n 140”)”) comprising the robotic system (Fig. 1 shows AMR 130 can communicate with other AMRs 140 through network 122; [0038] “The network environment 100 (also referred to as “system” herein) includes a server 102, a client device 110, a first AMR A 130, a second AMR n 140 (generally referred to as “AMRs” herein), and a database or data store 116, all coupled via a network 122.”).
Regarding claim 16, Go further teaches:
wherein the robotic system comprises a mobile logistics robot comprising a mobile chassis (Fig. 8B; [0105] “main body 830”) having a drive system that includes two or more independently controllable wheels, tracks, or other propulsive drive elements (Fig. 8B shows two wheels 822; [0103] “motion device (s) 822 (e.g., motors, wheels, tracks, etc.)”).
Regarding claim 17, Go further teaches:
wherein the robotic system comprises a mobile logistics robot (Fig. 1; [0038] “a first AMR A 130, a second AMR n 140”) comprising a mobile chassis (Fig. 8B; [0105] “main body 830”) and the processor is further configured to cause the mobile logistics robot to use the mobile chassis to move to a location associated with performing autonomously said tasks associated with the selected robotic application ([0062] “In order for the AMR 130 to perform the one or more tasks 212, the AMR may traverse a dynamic route 204 having one or more obstacles and/or turns associated therewith. The AMR 130 may begin physical traversal of the dynamic route 204 at Location A and arrive at Location B, in proximity of the physical device 210 . Thereafter, the AMR 130 may perform one or more processing tasks associated with the robotic tasks 212.”).
Regarding claim 18, Go teaches:
A method to control a multi-purpose mobile logistics robot ([0035]-[0036] disclose autonomous mobile robot (AMR)), comprising:
receiving an indication ([0072] “where at least one robotic task is identified for an associated AMR.”) to perform tasks ([0072] “a plurality of sub-tasks ... processing sensor data, processing visual/camera data, processing navigation data, processing obstacle avoidance data, and other processing tasks”) associated with a selected one of the plurality of robotic applications ([0072] discloses processing tasks as an example of a robotic application);
using a stored configuration information to determine a required software configuration ... associated with the selected robotic application ([0048] “For example, for a search and report task, an AMR can re-use two containerized software packages, (e.g., one handles object detection from a vision sensor, and, one handles the exploring and searching motion); [0051] “the server 102 can deploy containerized software installation packages (e.g., 106 and 108 ) thereon such that the packages may be executed. Furthermore, the server 102 may direct installation and deployment of containerized software installation packages onto any AMR, e.g., AMRs 130 and 140 . For example, the containerized software installation package 106 may be retrieved from the data store 116 and deployed at the server 102 and the AMR 130 (illustrated as package 106 ′). Additionally, the containerized software installation package 108 may be retrieved from the data store 116 and deployed at the server 102 and the AMR 140 (illustrated as package 108’).”);
updating a current software configuration ... of the robotic system as needed to match the required software configuration ... ([0048] “For example, for a search and report task, an AMR can re-use two containerized software packages, (e.g., one handles object detection from a vision sensor, and, one handles the exploring and searching motion); [0051] “the server 102 can deploy containerized software installation packages (e.g., 106 and 108 ) thereon such that the packages may be executed. Furthermore, the server 102 may direct installation and deployment of containerized software installation packages onto any AMR, e.g., AMRs 130 and 140 . For example, the containerized software installation package 106 may be retrieved from the data store 116 and deployed at the server 102 and the AMR 130 (illustrated as package 106 ′). Additionally, the containerized software installation package 108 may be retrieved from the data store 116 and deployed at the server 102 and the AMR 140 (illustrated as package 108’).”; [0094] “At block 704 , the containerized software package is deployed at the AMR. For example, the AMR may install, initialize, and execute all or some of the containerized software package. Block 704 is followed by block 706.”); and
using the updated software configuration ... to is autonomously perform tasks associated with the selected robotic application ([0057] “ each AMR may include an operating system 132, 142, a navigation system 134, 144 , and one or more containerized software installation packages 106′, 108′, as described above. Generally, the operating system 132, 142 may be an operating system including all suitable software components to enable initialization and use of the AMR. Additionally, the navigation system 134, 144 may be a software system configured to aid and direct the AMR to navigate a physical environment through obstacle avoidance, mapping, route planning, sensor data, and other aspects.”; [0097] “the robotic tasks completed by the AMR, utilizing the results received from the server 102.”).
Go does not specifically teach using the stored configuration information to determine a required hardware configuration associated with the selected robotic application, updating a current hardware configuration of the robotic system as needed to match the required hardware configuration, and using the updated hardware configuration to is autonomously perform tasks associated with the selected robotic application.
However, in the same field of endeavor, Matsuoka teaches:
using the stored configuration information to determine a required hardware configuration associated with the selected robotic application ([0056] “When the derivation is successful for the existing tool, the corresponding object and the plan can be implemented next. When none of the remaining target objects are appropriate for the currently connected tool, the robotic system 100 can plan for implementing the tool change operation at the end of the ongoing or preceding implementation of the plan. In alternative embodiments, the robotic system 100 can derive and evaluate feasibility and costs of all available tools for each targeted object.”; [0063] “The flat-posed objects 502 can correspond to the targeted objects having an orientation (e.g., a bottom surface of the object) parallel to a bottom surface of the start bin 322 . Accordingly, the standard grasp scenario 500 can correspond to the standard-fixed gripping tool 440.”; [0064] “he angled grasp scenario 510 can be for gripping angled object 512 . The angled object 512 can include objects leaning or resting on uneven contact points (e.g., resting along a non-horizontal plane) and/or objects having non-parallel opposing surfaces. In some embodiments, the angled object 512 can correspond to objects with poses having one or more surfaces oriented along angled directions/planes relative to horizontal/vertical reference directions. Accordingly, the angled grasp scenario 510 can correspond to the fixed-angle gripping tool 450.”),
updating a current hardware configuration of the robotic system as needed to match the required hardware configuration ([0056] “During implementation of the first plan, the system manager 302 can interact with the planner 304 to plan for a second object. When the derivation fails, the system manager 302 can select and interact to plan for different objects in an iterative manner in parallel to implementation of the preceding plan. When the derivation is successful for the existing tool, the corresponding object and the plan can be implemented next. When none of the remaining target objects are appropriate for the currently connected too, the robotic system 100 can plan for implementing the tool change operation at the end of the ongoing or preceding implementation of the plan. In alternative embodiments, the robotic system 100 can derive and evaluate feasibility and costs of all available tools for each targeted object.”), and
using the updated hardware configuration to is autonomously perform tasks associated with the selected robotic application ([0056] “During implementation of the first plan, the system manager 302 can interact with the planner 304 to plan for a second object. When the derivation fails, the system manager 302 can select and interact to plan for different objects in an iterative manner in parallel to implementation of the preceding plan. When the derivation is successful for the existing tool, the corresponding object and the plan can be implemented next. When none of the remaining target objects are appropriate for the currently connected too, the robotic system 100 can plan for implementing the tool change operation at the end of the ongoing or preceding implementation of the plan. In alternative embodiments, the robotic system 100 can derive and evaluate feasibility and costs of all available tools for each targeted object.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Go to use the stored configuration information to determine a required hardware configuration associated with the selected robotic application, update a current hardware configuration of the robotic system as needed to match the required hardware configuration, and use the updated hardware configuration to is autonomously perform tasks associated with the selected robotic application, as taught by Matsuoka. Such modification utilizes a set of tools, e.g. specialized end-effectors, to perform different tasks using the same robot and/or improves the performance of a given task, as stated by Matsuoka in [0050].
Regarding claim 19, Go further teaches:
wherein the mobile logistics robot (Fig. 8B) comprises a mobile chassis (Fig. 8B; [0105] “main body 830”) and one or more robotic arms mounted on the mobile chassis ([0046] “manipulation (e.g., using a tool, arm, sprayer, lamp, or other component) of portions of the AMR”; [0106] “although other motion devices such as: ... end-of-arm tooling ...”).
Regarding claim 20, Go teaches:
A computer program product embodied in a non-transitory computer readable medium and comprising computer instructions ([0118] “One or more methods described herein (e.g., methods 400, 600, and/or 700) can be implemented by computer program instructions or code, which can be executed on a computer. For example, the code can be implemented by one or more digital processors (e.g., microprocessors or other processing circuitry), and can be stored on a computer program product”) for:
receiving an indication ([0072] “where at least one robotic task is identified for an associated AMR.”) to perform tasks ([0072] “a plurality of sub-tasks ... processing sensor data, processing visual/camera data, processing navigation data, processing obstacle avoidance data, and other processing tasks”) associated with a selected one of the plurality of robotic applications ([0072] discloses processing tasks as an example of a robotic application);
using a stored configuration information to determine a required software configuration ... associated with the selected robotic application ([0048] “For example, for a search and report task, an AMR can re-use two containerized software packages, (e.g., one handles object detection from a vision sensor, and, one handles the exploring and searching motion); [0051] “the server 102 can deploy containerized software installation packages (e.g., 106 and 108 ) thereon such that the packages may be executed. Furthermore, the server 102 may direct installation and deployment of containerized software installation packages onto any AMR, e.g., AMRs 130 and 140 . For example, the containerized software installation package 106 may be retrieved from the data store 116 and deployed at the server 102 and the AMR 130 (illustrated as package 106 ′). Additionally, the containerized software installation package 108 may be retrieved from the data store 116 and deployed at the server 102 and the AMR 140 (illustrated as package 108’).”);
updating a current software configuration ... of the robotic system as needed to match the required software configuration ... ([0048] “For example, for a search and report task, an AMR can re-use two containerized software packages, (e.g., one handles object detection from a vision sensor, and, one handles the exploring and searching motion); [0051] “the server 102 can deploy containerized software installation packages (e.g., 106 and 108 ) thereon such that the packages may be executed. Furthermore, the server 102 may direct installation and deployment of containerized software installation packages onto any AMR, e.g., AMRs 130 and 140 . For example, the containerized software installation package 106 may be retrieved from the data store 116 and deployed at the server 102 and the AMR 130 (illustrated as package 106 ′). Additionally, the containerized software installation package 108 may be retrieved from the data store 116 and deployed at the server 102 and the AMR 140 (illustrated as package 108’).”; [0094] “At block 704 , the containerized software package is deployed at the AMR. For example, the AMR may install, initialize, and execute all or some of the containerized software package. Block 704 is followed by block 706.”); and
using the updated software configuration ... to is autonomously perform tasks associated with the selected robotic application ([0057] “ each AMR may include an operating system 132, 142, a navigation system 134, 144 , and one or more containerized software installation packages 106′, 108′, as described above. Generally, the operating system 132, 142 may be an operating system including all suitable software components to enable initialization and use of the AMR. Additionally, the navigation system 134, 144 may be a software system configured to aid and direct the AMR to navigate a physical environment through obstacle avoidance, mapping, route planning, sensor data, and other aspects.”; [0097] “the robotic tasks completed by the AMR, utilizing the results received from the server 102.”).
Go does not specifically teach using the stored configuration information to determine a required hardware configuration associated with the selected robotic application, updating a current hardware configuration of the robotic system as needed to match the required hardware configuration, and using the updated hardware configuration to is autonomously perform tasks associated with the selected robotic application.
However, in the same field of endeavor, Matsuoka teaches:
using the stored configuration information to determine a required hardware configuration associated with the selected robotic application ([0056] “When the derivation is successful for the existing tool, the corresponding object and the plan can be implemented next. When none of the remaining target objects are appropriate for the currently connected tool, the robotic system 100 can plan for implementing the tool change operation at the end of the ongoing or preceding implementation of the plan. In alternative embodiments, the robotic system 100 can derive and evaluate feasibility and costs of all available tools for each targeted object.”; [0063] “The flat-posed objects 502 can correspond to the targeted objects having an orientation (e.g., a bottom surface of the object) parallel to a bottom surface of the start bin 322 . Accordingly, the standard grasp scenario 500 can correspond to the standard-fixed gripping tool 440.”; [0064] “he angled grasp scenario 510 can be for gripping angled object 512 . The angled object 512 can include objects leaning or resting on uneven contact points (e.g., resting along a non-horizontal plane) and/or objects having non-parallel opposing surfaces. In some embodiments, the angled object 512 can correspond to objects with poses having one or more surfaces oriented along angled directions/planes relative to horizontal/vertical reference directions. Accordingly, the angled grasp scenario 510 can correspond to the fixed-angle gripping tool 450.”),
updating a current hardware configuration of the robotic system as needed to match the required hardware configuration ([0056] “During implementation of the first plan, the system manager 302 can interact with the planner 304 to plan for a second object. When the derivation fails, the system manager 302 can select and interact to plan for different objects in an iterative manner in parallel to implementation of the preceding plan. When the derivation is successful for the existing tool, the corresponding object and the plan can be implemented next. When none of the remaining target objects are appropriate for the currently connected too, the robotic system 100 can plan for implementing the tool change operation at the end of the ongoing or preceding implementation of the plan. In alternative embodiments, the robotic system 100 can derive and evaluate feasibility and costs of all available tools for each targeted object.”), and
using the updated hardware configuration to is autonomously perform tasks associated with the selected robotic application ([0056] “During implementation of the first plan, the system manager 302 can interact with the planner 304 to plan for a second object. When the derivation fails, the system manager 302 can select and interact to plan for different objects in an iterative manner in parallel to implementation of the preceding plan. When the derivation is successful for the existing tool, the corresponding object and the plan can be implemented next. When none of the remaining target objects are appropriate for the currently connected too, the robotic system 100 can plan for implementing the tool change operation at the end of the ongoing or preceding implementation of the plan. In alternative embodiments, the robotic system 100 can derive and evaluate feasibility and costs of all available tools for each targeted object.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Go to use the stored configuration information to determine a required hardware configuration associated with the selected robotic application, update a current hardware configuration of the robotic system as needed to match the required hardware configuration, and use the updated hardware configuration to is autonomously perform tasks associated with the selected robotic application, as taught by Matsuoka. Such modification utilizes a set of tools, e.g. specialized end-effectors, to perform different tasks using the same robot and/or improves the performance of a given task, as stated by Matsuoka in [0050].
Claims 4-6 are rejected under 35 U.S.C. 103 as being unpatentable over Go et al. (US 2022/0350582 A1), in view of Matsuoka et al. (US 2022/0135346 A1), and further in view of Yamazaki (US 2016/0031084 A1).
Regarding claim 4, neither Go nor Matsuoka specifically teaches wherein the mobile logistics robot includes two or more robotic arms at least two of which have different end effectors.
However, in the same field of endeavor, Yamazaki teaches:
wherein the mobile logistics robot includes two or more robotic arms (Fig. 1; [0057] “a first articulated arm (simply referred to as a “first arm”) 230 and a second articulated arm (simply referred to as a “second arm”) 240”) at least two of which have different end effectors ([0065] “The end effectors 610 and 620 are portions corresponding to human hands, and have a function of gripping an object, for example. A configuration of the end effectors 610 and 620 varies depending on work to be carried out.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Go, in view of Matsuoka, to include two or more robotic arms at least two of which have different end effectors, as taught by Yamazaki, in order to increase work output.
Regarding claim 5, the teachings of Go in view of Matsuoka and Yamazaki have been discussed above with respect to claim 4. Go does not specifically teach wherein the different end effectors are prescribed by the required hardware configuration.
However, Matsuoka teaches:
wherein the different end effectors are prescribed by the required hardware configuration ([0050] “ In some embodiments, the robotic system 100 can utilize a set of tools (e.g., specialized end-effectors) to perform different tasks using the same robot and/or improve the performance of a given task. For example, the robotic system 100 can selectively connect the robotic arm 306 to a gripper, a welder, or a cutter to perform corresponding functions according to the assigned task.”; [0052] “In utilizing the set of tools, the system manager 302 can provide a target selection 313 to the planner 304 to identify the tool and/or the target object 112 selected for one or more of the tasks/objects.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Go, in view of Matsuoka and Yamazaki, to prescribe the different end effectors by the required hardware configuration, as taught by Matsuoka, in order to select a suitable end effector to perform corresponding functions according to an assigned task.
Regarding claim 6, the teachings of Go in view of Matsuoka and Yamazaki have been discussed above with respect to claim 5. Go does not specifically teach wherein the processor is configured to cause the end effectors to be mounted on the robotic arms based at least in part on the required hardware configuration.
However, Matsuoka teaches:
wherein the processor is configured to cause the end effectors to be mounted on the robotic arms based at least in part on the required hardware configuration ([0050] “ In some embodiments, the robotic system 100 can utilize a set of tools (e.g., specialized end-effectors) to perform different tasks using the same robot and/or improve the performance of a given task. For example, the robotic system 100 can selectively connect the robotic arm 306 to a gripper, a welder, or a cutter to perform corresponding functions according to the assigned task.”; [0052] “In utilizing the set of tools, the system manager 302 can provide a target selection 313 to the planner 304 to identify the tool and/or the target object 112 selected for one or more of the tasks/objects.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Go, in view of Matsuoka and Yamazaki, to cause the end effectors to be mounted on the robotic arms based at least in part on the required hardware configuration, as taught by Matsuoka, in order to select a suitable end effector to perform corresponding functions according to an assigned task.
Claims 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Go et al. (US 2022/0350582 A1), in view of Matsuoka et al. (US 2022/0135346 A1), and further in view of Murphy et al. (US 2022/0305667 A1).
Regarding claim 14, the teachings of Go in view of Matsuoka have been discussed above with respect to claim 1. Go further teaches wherein the robotic system comprises a mobile logistics robot comprising a mobile chassis (Fig. 8B; [0105] “main body 830”).
Neither Go nor Matsuoka specifically teaches the mobile chassis having a width equal to or less than 36 inches.
However, in the same field of endeavor, Murphy teaches wherein the robotic system comprises a mobile logistics robot comprising a mobile chassis having a small footprint ([0033] “Also of note in FIG. 2B is that the robot 20 a is working alongside humans (e.g., workers 27a and 27b ). Given that the robot 20 a is configured to perform many tasks that have traditionally been performed by humans, the robot 20a is designed to have a small footprint, both to enable access to areas designed to be accessed by humans, and to minimize the size of a safety zone around the robot into which humans are prevented from entering.”).
Even though Murphy does not explicitly teach the mobile chassis having a width of equal to or less than 36 inches, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Go, in view of Matsuoka and Murphy, to configure the mobile chassis having a width equal to or less than 36 inches, since it has been held that where general conditions of a claim are disclosed in the prior art, discovering the optimum or working ranges involves only routine skill in the art. In re Aller, 105 USPQ 233. Such modification further enables access to areas designed to be accessed by humans, and minimizes the size of a safety zone around the robot into which humans are prevented from entering, as stated by Murphy in [0033].
Regarding claim 15, Go further teaches wherein the mobile logistics robot comprises one or more robotic arms mounted on the mobile chassis ([0046] “manipulation (e.g., using a tool, arm, sprayer, lamp, or other component) of portions of the AMR”; [0106] “although other motion devices such as: ... end-of-arm tooling ...”).
Neither Go nor Matsuoka specifically teaches the processor is further configured to cause the mobile logistics robot to place each of the one or more robotic arms in a stowed position to facilitate transit through a space constrained area.
However, Murphy teaches:
the processor is further configured to cause the mobile logistics robot to place each of the one or more robotic arms in a stowed position to facilitate transit through a space constrained area ([0055] “As such, the arm may be stowed (e.g., retracted into the footprint of the base and powered down) during such navigation. In this operating configuration, the spatial extent and the speed of the arm are reduced, and thus the size of the robot's overall buffer zone may be reduced accordingly, allowing the robot to enter more confined areas safely.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Go, in view of Matsuoka and Murphy, to cause the mobile logistics robot to place each of the one or more robotic arms in a stowed position to facilitate transit through a space constrained area., as taught by Murphy. Such modification reduces spatial extend and speed of the arm, thus reducing the size of the robot’s overall buffer zone according and allowing the robot to enter more confined areas safely, as stated by Murphy in [0055].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Saboo et al. (US 2016/0129592 A1) teaches methods and systems for dynamically maintaining a map of robotic devices in an environment.
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/NHI Q BUI/Primary Examiner, Art Unit 3656