公开(公告)号：US20230256595A1

公开(公告)日：2023-08-17

申请号：US17856699

申请日：2022-07-01

Applicant: NVIDIA CORPORATION

Inventor： Adithyavairavan MURALI ,  Balakumar SUNDARALINGAM ,  Yun-Chun CHEN ,  Dieter FOX ,  Animesh GARG

IPC: B25J9/16

CPC classification number: B25J9/163 ,  B25J9/161 ,  B25J9/1666 ,  B25J9/1669 ,  B25J9/1697 ,  B25J9/1653

Abstract: One embodiment of a method for controlling a robot includes receiving sensor data associated with an environment that includes an object; applying a machine learning model to a portion of the sensor data associated with the object and one or more trajectories of motion of the robot to determine one or more path lengths of the one or more trajectories; generating a new trajectory of motion of the robot based on the one or more trajectories and the one or more path lengths; and causing the robot to perform one or more movements based on the new trajectory.

公开(公告)号：US20240095527A1

公开(公告)日：2024-03-21

申请号：US18448049

申请日：2023-08-10

Applicant: NVIDIA CORPORATION

Inventor： Ankur HANDA ,  Gavriel STATE ,  Arthur David ALLSHIRE ,  Dieter FOX ,  Jean-Francois Victor LAFLECHE ,  Jingzhou LIU ,  Viktor MAKOVIICHUK ,  Yashraj Shyam NARANG ,  Aleksei Vladimirovich PETRENKO ,  Ritvik SINGH ,  Balakumar SUNDARALINGAM ,  Karl VAN WYK ,  Alexander ZHURKEVICH

IPC: G06N3/08

CPC classification number: G06N3/08

Abstract: Systems and techniques are described related to training one or more machine learning models for use in control of a robot. In at least one embodiment, one or more machine learning models are trained based at least on simulations of the robot and renderings of such simulations—which may be performed using one or more ray tracing algorithms, operations, or techniques.

公开(公告)号：US20250104277A1

公开(公告)日：2025-03-27

申请号：US18608804

申请日：2024-03-18

Applicant: NVIDIA CORPORATION

Inventor： Jonathan TREMBLAY ,  Stanley BIRCHFIELD ,  Valts BLUKIS ,  Balakumar SUNDARALINGAM ,  Stephen TYREE ,  Bowen WEN

IPC: G06T7/73 ,  G06T15/04

Abstract: One embodiment of a method for determining object poses includes receiving first sensor data and second sensor data, where the first sensor data is associated with a first modality, and the second sensor data is associated with a second modality that is different from the first modality, and performing one or more iterative operations to determine a pose of an object based on one or more comparisons of (i) one or more renderings of a three-dimensional (3D) representation of the object in the first modality with the first sensor data, and (ii) one or more renderings of the 3D representation of the object in the second modality with the second sensor data.

公开(公告)号：US20250083309A1

公开(公告)日：2025-03-13

申请号：US18646312

申请日：2024-04-25

Applicant: NVIDIA Corporation

Inventor： Nathan Donald RATLIFF ,  Karl VAN WYK ,  Ankur HANDA ,  Viktor MAKOVIICHUK ,  Yijie GUO ,  Jie XU ,  Tyler LUM ,  Balakumar SUNDARALINGAM ,  Jingzhou LIU

IPC: B25J9/16

Abstract: In various examples, systems and methods are disclosed relating to geometric fabrics for accelerated policy learning and sim-to-real transfer in robotics systems, platforms, and/or applications. For example, a system can provide an input indicative of a goal pose for a robot to a model to cause the model to generate an output, the output representing a plurality of points along a path for movement of the robot to the goal pose; and generate one or more control signals for operation of the robot based at least on the plurality of points along the path and a policy corresponding to one or more criteria for the operation of the robot. In examples, the system can provide the one or more control signals to the robot to cause the robot to move toward the goal pose.

公开(公告)号：US20240338598A1

公开(公告)日：2024-10-10

申请号：US18606938

申请日：2024-03-15

Applicant: NVIDIA CORPORATION

Inventor： Caelan Reed GARRETT ,  Fabio TOZETO RAMOS ,  Iretiayo AKINOLA ,  Alperen DEGIRMENCI ,  Clemens EPPNER ,  Dieter FOX ,  Tucker Ryer HERMANS ,  Ajay Uday MANDLEKAR ,  Arsalan MOUSAVIAN ,  Yashraj Shyam NARANG ,  Rowland Wilde O'FLAHERTY ,  Balakumar SUNDARALINGAM ,  Wei YANG

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: One embodiment of a method for generating simulation data to train a machine learning model includes generating a plurality of simulation environments based on a user input, and for each simulation environment included in the plurality of simulation environments: generating a plurality of tasks for a robot to perform within the simulation environment, performing one or more operations to determine a plurality of robot trajectories for performing the plurality of tasks, and generating simulation data for training a machine learning model by performing one or more operations to simulate the robot moving within the simulation environment according to the plurality of trajectories.

公开(公告)号：US20240066710A1

公开(公告)日：2024-02-29

申请号：US18168482

申请日：2023-02-13

Applicant: NVIDIA CORPORATION

Inventor： Balakumar SUNDARALINGAM ,  Stanley BIRCHFIELD ,  Zhenggang TANG ,  Jonathan TREMBLAY ,  Stephen TYREE ,  Bowen WEN ,  Ye YUAN ,  Charles LOOP

IPC: B25J9/16 ,  B25J19/02

CPC classification number: B25J9/1697 ,  B25J9/163 ,  B25J9/1664 ,  B25J9/1676 ,  B25J19/023

Abstract: One embodiment of a method for controlling a robot includes generating a representation of spatial occupancy within an environment based on a plurality of red, green, blue (RGB) images of the environment, determining one or more actions for the robot based on the representation of spatial occupancy and a goal, and causing the robot to perform at least a portion of a movement based on the one or more actions.