Nvidia Corporation

Byron Boots

Dieter Fox

Animesh Garg

Stan Birchfield

Fabio Tozeto Ramos

Ankur Handa

Balakumar Sundaralingam

Nathan Donald Ratliff

Adam Harper Fishman

Ajay Uday Mandlekar

Alexander Conrad Lambert

Alexander Lambert

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.

Controlling position of robot by determining goal proposals by using neural networks

Apparatuses, systems, and techniques to infer a sequence of actions to perform using one or more neural networks trained, at least in part, by optimizing a probability distribution function using a cost function, wherein the probability distribution represents different sequences of actions that can be performed. In at least one embodiment, a model predictive control problem is formulated as a Bayesian inference task to infer a set of solutions.

Model predictive control techniques for autonomous systems

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Byron Boots