VMP: Versatile Motion Priors for Robustly Tracking Motion on Physical Characters

Serifi, Agon; Grandia, Ruben; Knoop, Espen; Gross, Markus; Bächer, Moritz

VMP: Versatile Motion Priors for Robustly Tracking Motion on Physical Characters

Date

2024

Authors

Serifi, Agon
Grandia, Ruben
Knoop, Espen
Gross, Markus
Bächer, Moritz

Publisher

The Eurographics Association and John Wiley & Sons Ltd.

Abstract

Recent progress in physics-based character control has made it possible to learn policies from unstructured motion data. However, it remains challenging to train a single control policy that works with diverse and unseen motions, and can be deployed to real-world physical robots. In this paper, we propose a two-stage technique that enables the control of a character with a full-body kinematic motion reference, with a focus on imitation accuracy. In a first stage, we extract a latent space encoding by training a variational autoencoder, taking short windows of motion from unstructured data as input. We then use the embedding from the time-varying latent code to train a conditional policy in a second stage, providing a mapping from kinematic input to dynamics-aware output. By keeping the two stages separate, we benefit from self-supervised methods to get better latent codes and explicit imitation rewards to avoid mode collapse. We demonstrate the efficiency and robustness of our method in simulation, with unseen user-specified motions, and on a bipedal robot, where we bring dynamic motions to the real world.

CCS Concepts: Computing methodologies → Learning from demonstrations; Learning latent representations; Reinforcement learning; Physical simulation; Animation; Control methods

        @article{10.1111:cgf.15175
,
journal = {Computer Graphics Forum},
title = {{VMP: Versatile Motion Priors for Robustly Tracking Motion on Physical Characters
}},
author = {Serifi, Agon and 
Grandia, Ruben and 
Knoop, Espen and 
Gross, Markus and 
Bächer, Moritz
},
year = {2024
},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.
},
ISSN = {1467-8659
},
DOI = {10.1111/cgf.15175
}
}