Massachusetts Institute of Technology

Toyota Research Institute, Inc.

Brian C Williams

Guy Rosman

John J Leonard

Xin Huang

Stephen G McGill

Luke S Fletcher

Igor Gilitschenski

Stephen G Mcgill

Jonathan A DeCastro

Ashkan Mohammadzadeh Jasour

Systems and methods for predicting a trajectory of a moving object are disclosed herein. One embodiment downloads, to a robot, a probabilistic hybrid discrete-continuous automaton (PHA) model learned as a deep neural network; uses the deep neural network to infer a sequence of high-level discrete modes and a set of associated low-level samples, wherein the high-level discrete modes correspond to candidate maneuvers for the moving object and the low-level samples are candidate trajectories; uses the sequence of high-level discrete modes and the set of associated low-level samples, via a learned proposal distribution in the deep neural network, to adaptively sample the sequence of high-level discrete modes to produce a reduced set of low-level samples; applies a sample selection technique to the reduced set of low-level samples to select a predicted trajectory for the moving object; and controls operation of the robot based, at least in part, on the predicted trajectory.

Systems and methods for predicting the trajectory of a moving object

A system and method for generating a predicted vehicle trajectory includes a generative adversarial network configured to receive a trajectory vector of a target vehicle and generate a set of latent state vectors using the received trajectory vector and an artificial neural network. The latent state vectors each comprise a high-level sub-vector, Z. The GAN enforces Zto be correlated to an annotation coding representing semantic categories of vehicle trajectories. The GAN selects a subset, from the set of latent state vectors, using farthest point sampling and generates a predicted vehicle trajectory based on the selected subset of latent state vectors.

Methods and systems for diversity-aware vehicle motion prediction via latent semantic sampling

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Cambridge, MA, United States of America

Brian C Williams