Leland Stanford Junior University

Toyota Research Institute, Inc.

Amine Elhafsi

Adrien David Gaidon

Guy Rosman

Marco Pavone

Boris Ivanovic

A mobile robot can be caused to move according to a planned trajectory. The mobile robot can be a vehicle. Information about agents in an environment of the mobile robot can be received from sensors. At a first time, a spatiotemporal graph can be produced. The spatiotemporal graph can represent relationships among the agents in the environment. The mobile robot can be one of the agents in the environment. Information from the spatiotemporal graph can be input to neural networks to produce information for a mixture of affine time-varying systems. The mixture of affine time-varying systems can represent an evolution of agent states of the agents. Using the mixture of affine time-varying systems and information associated with the first time, a prediction of the agent states at a second time can be calculated. The mobile robot can be caused to move according to the planned trajectory determined from the prediction.

Causing a mobile robot to move according to a planned trajectory determined from a prediction of agent states of agents in an environment of the mobile robot

Growing community of inventors

Riverside, CA, United States of America

Amine Elhafsi