公开(公告)号：US11893468B2

公开(公告)日：2024-02-06

申请号：US16931211

申请日：2020-07-16

Applicant: NVIDIA Corporation

Inventor： Yu-Wei Chao ,  De-An Huang ,  Christopher Jason Paxton ,  Animesh Garg ,  Dieter Fox

IPC: G06N3/008 ,  G06N20/00

CPC classification number: G06N3/008 ,  G06N20/00

Abstract: Apparatuses, systems, and techniques to identify a goal of a demonstration. In at least one embodiment, video data of a demonstration is analyzed to identify a goal. Object trajectories identified in the video data are analyzed with respect to a task predicate satisfied by a respective object trajectory, and with respect to motion predicate. Analysis of the trajectory with respect to the motion predicate is used to assess intentionality of a trajectory with respect to the goal.

公开(公告)号：US20220382246A1

公开(公告)日：2022-12-01

申请号：US17732313

申请日：2022-04-28

Applicant: NVIDIA Corporation

Inventor： Eric Heiden ,  Fabio Tozeto Ramos ,  Yashraj Narang ,  Miles Macklin ,  Dieter Fox ,  Animesh Garg ,  Mike Skolones

IPC: G05B19/4069 ,  G06T17/20 ,  G05B19/416 ,  B25J9/16

Abstract: A differentiable simulator for simulating the cutting of soft materials by a cutting instrument is provided. In accordance with one aspect of the disclosure, a method for simulating a cutting operation includes: receiving a mesh for an object, modifying the mesh to add virtual nodes associated with a predefined cutting plane, optimizing a set of parameters associated with a simulator based on ground-truth data, and running a simulation via the simulator to generate outputs that include trajectories associated with a cutting instrument. Optimizing the set of parameters can include performing inference based on a set of ground-truth trajectories captured using sensors to measure real-world cutting operations. The inference techniques can employ stochastic gradient descent, stochastic gradient Langevin dynamics, or a Bayesian approach. In an embodiment, the simulator can be utilized to generate control signals for a robot based on the simulated trajectories.

公开(公告)号：US20220055689A1

公开(公告)日：2022-02-24

申请号：US16998941

申请日：2020-08-20

Applicant: NVIDIA Corporation

Inventor： Ajay Uday Mandlekar ,  Fabio Tozeto Ramos ,  Byron Boots ,  Animesh Garg ,  Dieter Fox

IPC: B62D15/02 ,  B60W30/06 ,  B60W60/00 ,  G06N3/04 ,  G06N3/08

Abstract: A framework for offline learning from a set of diverse and suboptimal demonstrations operates by selectively imitating local sequences from the dataset. At least one embodiment recovers performant policies from large manipulation datasets by decomposing the problem into a goal-conditioned imitation and a high-level goal selection mechanism.

公开(公告)号：US20210064925A1

公开(公告)日：2021-03-04

申请号：US16558620

申请日：2019-09-03

Applicant: Nvidia Corporation

Inventor： Kevin Shih ,  Aysegul Dundar ,  Animesh Garg ,  Robert Pottorff ,  Andrew Tao ,  Bryan Catanzaro

IPC: G06K9/62 ,  G06N3/04 ,  G06N3/08

Abstract: Apparatuses, systems, and techniques to enhance video are disclosed. In at least one embodiment, one or more neural networks are used to create, from a first video, a second video having one or more additional video frames.