公开(公告)号：US20210110089A1

公开(公告)日：2021-04-15

申请号：US16916017

申请日：2020-06-29

Applicant: NVIDIA Corporation

Inventor： Carolyn Linjon Chen ,  Yashraj Shyam Narang ,  Fabio Tozeto Ramos ,  Dieter Fox

IPC: G06F30/27 ,  G06N7/00 ,  G06N3/08 ,  G06K9/62 ,  G06T7/77 ,  G06T7/00 ,  B25J11/00 ,  B25J9/16

Abstract: Apparatuses, systems, and techniques to identify at least one physical characteristic of materials from computer simulations of manipulations of materials. In at least one embodiment, physical characteristics are determined by comparing measured statistics of observed manipulations to simulations of manipulations using a simulator trained with a likelihood-free inference engine.

公开(公告)号：US20200368906A1

公开(公告)日：2020-11-26

申请号：US16417540

申请日：2019-05-20

Applicant: NVIDIA Corporation

Inventor： Fabio Tozeto Ramos ,  Dieter Fox

IPC: B25J9/16 ,  G05B13/04

Abstract: In an embodiment, a system calculates a distribution of possible parameters for a simulation that cause the simulation to match a measured behavior in the real world. In an embodiment, the system selects a plurality of simulation parameters based on a statistical distribution that represents an initial estimate of possible parameter values. In an embodiment, using the results produced by the simulation, an updated distribution of possible parameters is constructed based on a density of the results modeled using Fourier features. In an embodiment, the updated distribution of possible parameters can be used to select a particular set of parameters for the simulation, which cause the simulator approximate the measured behavior.

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.

公开(公告)号：US12223949B2

公开(公告)日：2025-02-11

申请号：US17930349

申请日：2022-09-07

Applicant: NVIDIA Corporation

Inventor： Christopher Jason Paxton ,  Weiyu Liu ,  Tucker Ryer Hermans ,  Dieter Fox

IPC: G06F40/30 ,  B25J13/00 ,  G10L15/18 ,  G10L15/22

Abstract: A robotic system is provided for performing rearrangement tasks guided by a natural language instruction. The system can include a number of neural networks used to determine a selected rearrangement of the objects in accordance with the natural language instruction. A target object predictor network processes a point cloud of the scene and the natural language instruction to identify a set of query objects that are to-be-rearranged. A language conditioned prior network processes the point cloud, natural language instruction, and the set of query objects to sample a distribution of rearrangements to generate a number of sets of pose offsets for the set of query objects. A discriminator network then processes the samples to generate scores for the samples. The samples may be refined until a score for at least one of the sample generated by the discriminator network is above a threshold value.

公开(公告)号：US12122053B2

公开(公告)日：2024-10-22

申请号：US16916017

申请日：2020-06-29

Applicant: NVIDIA Corporation

Inventor： Carolyn Linjon Chen ,  Yashraj Shyam Narang ,  Fabio Tozeto Ramos ,  Dieter Fox

IPC: B25J9/16 ,  B25J11/00 ,  G01N15/00 ,  G06F17/18 ,  G06F18/214 ,  G06F30/27 ,  G06N3/08 ,  G06N7/01 ,  G06T7/00 ,  G06T7/77 ,  G06V10/764 ,  G06V10/82 ,  G06V20/56 ,  G06V20/64

CPC classification number: B25J9/1671 ,  B25J9/163 ,  B25J11/008 ,  G06F17/18 ,  G06F18/214 ,  G06F30/27 ,  G06N3/08 ,  G06N7/01 ,  G06T7/0004 ,  G06T7/77 ,  G06V10/764 ,  G06V10/82 ,  G06V20/56 ,  G06V20/64 ,  G01N15/00 ,  G06T2207/10028

Abstract: Apparatuses, systems, and techniques to identify at least one physical characteristic of materials from computer simulations of manipulations of materials. In at least one embodiment, physical characteristics are determined by comparing measured statistics of observed manipulations to simulations of manipulations using a simulator trained with a likelihood-free inference engine.

公开(公告)号：US20240153196A1

公开(公告)日：2024-05-09

申请号：US18218527

申请日：2023-07-05

Applicant: NVIDIA Corporation

Inventor： Valts Blukis ,  Taeyeop Lee ,  Jonathan Tremblay ,  Bowen Wen ,  Dieter Fox ,  Stanley Thomas Birchfield

IPC: G06T15/06 ,  G06T1/20 ,  G06T7/70 ,  G06T7/90 ,  G06V10/82 ,  H04N13/117

CPC classification number: G06T15/06 ,  G06T1/20 ,  G06T7/70 ,  G06T7/90 ,  G06V10/82 ,  H04N13/117 ,  G06T2207/10024 ,  G06V2201/07

Abstract: Apparatuses, systems, and techniques to generate an image of one or more objects. In at least one embodiment, an image of one or more objects is generated using a neural network based on, for example, a representation of a scene.

公开(公告)号：US20240123620A1

公开(公告)日：2024-04-18

申请号：US18219031

申请日：2023-07-06

Applicant: NVIDIA Corporation

Inventor： Jonathan Tremblay ,  Stanley Thomas Birchfield ,  Valts Blukis ,  Bowen Wen ,  Dieter Fox ,  Taeyeop Lee

IPC: B25J9/16

CPC classification number: B25J9/1669 ,  B25J9/161 ,  B25J9/1697

Abstract: Apparatuses, systems, and techniques to generate and select grasp proposals. In at least one embodiment, grasp proposals are generated and selected using one or more neural networks, based on, for example, a latent code corresponding to an object.

公开(公告)号：US20230294277A1

公开(公告)日：2023-09-21

申请号：US17854730

申请日：2022-06-30

Applicant: Nvidia Corporation

Inventor： Wei Yang ,  Balakumar Sundaralingam ,  Christopher Jason Paxton ,  Maya Cakmak ,  Yu-Wei Chao ,  Dieter Fox ,  Iretiayo Akinola

IPC: B25J9/16 ,  G05B19/4155

CPC classification number: B25J9/1612 ,  G05B19/4155 ,  B25J9/1666 ,  B25J9/1605 ,  G05B2219/50391 ,  G05B2219/40269

Abstract: Approaches presented herein provide for predictive control of a robot or automated assembly in performing a specific task. A task to be performed may depend on the location and orientation of the robot performing that task. A predictive control system can determine a state of a physical environment at each of a series of time steps, and can select an appropriate location and orientation at each of those time steps. At individual time steps, an optimization process can determine a sequence of future motions or accelerations to be taken that comply with one or more constraints on that motion. For example, at individual time steps, a respective action in the sequence may be performed, then another motion sequence predicted for a next time step, which can help drive robot motion based upon predicted future motion and allow for quick reactions.

公开(公告)号：US20230294276A1

公开(公告)日：2023-09-21

申请号：US18148548

申请日：2022-12-30

Applicant: Nvidia Corporation

Inventor： Yu-Wei Chao ,  Yu Xiang ,  Wei Yang ,  Dieter Fox ,  Chris Paxton ,  Balakumar Sundaralingam ,  Maya Cakmak

IPC: B25J9/16

CPC classification number: B25J9/1605 ,  B25J9/163 ,  G05B2219/39001

Abstract: Approaches presented herein provide for simulation of human motion for human-robot interactions, such as may involve a handover of an object. Motion capture can be performed for a hand grasping and moving an object to a location and orientation appropriate for a handover, without a need for a robot to be present or an actual handover to occur. This motion data can be used to separately model the hand and the object for use in a handover simulation, where a component such as a physics engine may be used to ensure realistic modeling of the motion or behavior. During a simulation, a robot control model or algorithm can predict an optimal location and orientation to grasp an object, and an optimal path to move to that location and orientation, using a control model or algorithm trained, based at least in part, using the motion models for the hand and object.

公开(公告)号：US20230202031A1

公开(公告)日：2023-06-29

申请号：US18116118

申请日：2023-03-01

Applicant: NVIDIA Corporation

Inventor： Wei Yang ,  Christopher Jason Paxton ,  Yu-Wei Chao ,  Dieter Fox

IPC: B25J9/16 ,  G06T7/50 ,  G06V20/30 ,  G06V20/64 ,  G06V40/10

CPC classification number: B25J9/1612 ,  G06T7/50 ,  G06V20/30 ,  G06V20/64 ,  G06V40/107 ,  G06T2207/10028 ,  B25J9/1697 ,  B25J9/16

Abstract: A robotic control system directs a robot to take an object from a human grasp by obtaining an image of a human hand holding an object, estimating the pose of the human hand and the object, and determining a grasp pose for the robot that will not interfere with the human hand. In at least one example, a depth camera is used to obtain a point cloud of the human hand holding the object. The point cloud is provided to a deep network that is trained to generate a grasp pose for a robotic gripper that can take the object from the human's hand without pinching or touching the human's fingers.