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公开(公告)号:US20250091207A1
公开(公告)日:2025-03-20
申请号:US18368927
申请日:2023-09-15
Applicant: NVIDIA Corporation
Inventor: Wentao Yuan , Adithyavairavan Murali , Arsalan Mousavian , Dieter Fox
IPC: B25J9/16
Abstract: Apparatuses, systems, and techniques to determine a grasp and placement of an object in an environment. In at least one embodiment, one or more neural networks are used to identify one or more grasping and placement masks used to manipulate an object.
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公开(公告)号:US20220292699A1
公开(公告)日:2022-09-15
申请号:US17195296
申请日:2021-03-08
Applicant: NVIDIA Corporation
Inventor: Luyang Zhu , Arsalan Mousavian , Yu Xiang , Dieter Fox
Abstract: Apparatuses, systems, and techniques to estimate or predict depth information for image data. In at least one embodiment, depth information is predicted based at least in part on color information and geometry information associated with an image.
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公开(公告)号:US12138805B2
公开(公告)日:2024-11-12
申请号:US17198082
申请日:2021-03-10
Applicant: NVIDIA Corporation
Inventor: Martin Sundermeyer , Arsalan Mousavian , Dieter Fox
Abstract: Apparatuses, systems, and techniques to grasp objects with a robot. In at least one embodiment, a neural network is trained to determine a grasp pose of an object within a cluttered scene using a point cloud generated by a depth camera.
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公开(公告)号:US20240096074A1
公开(公告)日:2024-03-21
申请号:US17581550
申请日:2022-01-21
Applicant: Nvidia Corporation
Inventor: Brian Okorn , Arsalan Mousavian , Lucas Manuelli , Dieter Fox
CPC classification number: G06V10/82 , G06V10/26 , G06V10/7715
Abstract: Apparatuses, systems, and techniques are presented to identify one or more objects. In at least one embodiment, one or more neural networks can be used to identify one or more objects based, at least in part, on one or more descriptors of one or more segments of the one or more objects.
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公开(公告)号:US11724401B2
公开(公告)日:2023-08-15
申请号:US16914105
申请日:2020-06-26
Applicant: NVIDIA Corporation
Inventor: Arsalan Mousavian , Clemens Eppner , Dieter Fox , Adithyavairavan Murali
IPC: G06K9/00 , B25J9/16 , G05B19/4155 , B25J13/08 , G06N3/08 , G06T7/50 , G06T7/10 , G06T7/70 , G05B19/402
CPC classification number: B25J9/1697 , B25J9/161 , B25J9/1612 , B25J9/1666 , B25J13/08 , G05B19/402 , G05B19/4155 , G06N3/08 , G06T7/10 , G06T7/50 , G06T7/70 , G05B2219/40269 , G06T2207/10028 , G06T2207/20084 , G06T2207/20132 , G06T2207/30244
Abstract: Apparatuses, systems, and techniques determine a set of grasp poses that would allow a robot to successfully grasp an object that is proximate to at least one additional object. In at least one embodiment, the set of grasp poses is modified based on a determination that at least one of the grasp poses in the set of grasp poses would interfere with at least one additional object that is proximate to the object.
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公开(公告)号:US12299800B2
公开(公告)日:2025-05-13
申请号:US18126900
申请日:2023-03-27
Applicant: NVIDIA Corporation
Inventor: Adithyavairavan Murali , Arsalan Mousavian , Clemens Eppner , Adam Fishman , Dieter Fox
Abstract: One common robotic task is the rearrangement of physical objects situated in an environment. This typically involves a robot manipulator picking up a target object and placing the target object in some target location, such as a shelf, cabinet or cubby, and requires the skills of picking, placing and generating complex collision-free motions, oftentimes in a cluttered environment. The present disclosure provides collision detection for object rearrangement using a three-dimensional (3D) scene representation.
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公开(公告)号:US20230234233A1
公开(公告)日:2023-07-27
申请号:US17585394
申请日:2022-01-26
Applicant: NVIDIA Corporation
Inventor: Ankit Goyal , Arsalan Mousavian , Christopher Jason Paxton , Yu-Wei Chao , Dieter Fox
CPC classification number: B25J9/1697 , G06T7/70 , G06T7/50 , G06T7/269 , G06T7/10 , B25J13/08 , G05B13/027 , G06T2207/10024 , G06T2207/20084 , B60W60/001
Abstract: Apparatuses, systems, and techniques to place one or more objects in a location and orientation. In at least one embodiment, one or more circuits are to use one or more neural networks to cause one or more autonomous devices to place one or more objects in a location and orientation based, at least in part, on one or more images of the location and orientation.
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公开(公告)号:US20210138655A1
公开(公告)日:2021-05-13
申请号:US16914105
申请日:2020-06-26
Applicant: NVIDIA Corporation
Inventor: Arsalan Mousavian , Clemens Eppner , Dieter Fox
IPC: B25J9/16 , G05B19/402 , G05B19/4155 , B25J13/08 , G06N3/08 , G06T7/50 , G06T7/10 , G06T7/70
Abstract: Apparatuses, systems, and techniques determine a set of grasp poses that would allow a robot to successfully grasp an object that is proximate to at least one additional object. In at least one embodiment, the set of grasp poses is modified based on a determination that at least one of the grasp poses in the set of grasp poses would interfere with at least one additional object that is proximate to the object.
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公开(公告)号:US20240095077A1
公开(公告)日:2024-03-21
申请号:US18122594
申请日:2023-03-16
Applicant: NVIDIA Corporation
Inventor: Ishika Singh , Arsalan Mousavian , Ankit Goyal , Danfei Xu , Jonathan Tremblay , Dieter Fox , Animesh Garg , Valts Blukis
CPC classification number: G06F9/5027 , G06N20/00
Abstract: Apparatuses, systems, and techniques to generate a prompt for one or more machine learning processes. In at least one embodiment, the machine learning process(es) generate(s) a plan to perform a task (identified in the prompt) that is to be performed by an agent (real world or virtual).
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公开(公告)号:US20240009851A1
公开(公告)日:2024-01-11
申请号:US18233624
申请日:2023-08-14
Applicant: NVIDIA Corporation
Inventor: Arsalan Mousavian , Clemens Eppner , Dieter Fox , Adithyavairavan Murali
IPC: B25J9/16 , G05B19/4155 , B25J13/08 , G06N3/08 , G06T7/50 , G06T7/10 , G06T7/70 , G05B19/402
CPC classification number: B25J9/1697 , G05B19/4155 , B25J13/08 , B25J9/1612 , B25J9/1666 , B25J9/161 , G06N3/08 , G06T7/50 , G06T7/10 , G06T7/70 , G05B19/402 , G06T2207/30244 , G05B2219/40269 , G06T2207/20084 , G06T2207/10028 , G06T2207/20132
Abstract: Apparatuses, systems, and techniques determine a set of grasp poses that would allow a robot to successfully grasp an object that is proximate to at least one additional object. In at least one embodiment, the set of grasp poses is modified based on a determination that at least one of the grasp poses in the set of grasp poses would interfere with at least one additional object that is proximate to the object.
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