Design and Control of a Bipedal Robotic Character

TL;DR

This paper presents a new bipedal robot designed for entertainment, combining expressive motion control via reinforcement learning with real-time operator interface to enable believable performances.

Contribution

It introduces a character-driven robot design and a reinforcement learning control system that allows expressive, artist-directed motions in real-time performances.

Findings

Successful execution of artistic motions conditioned on commands

Real-time blending of multiple animation sources

Enhanced human-robot engagement in entertainment contexts

Abstract

Legged robots have achieved impressive feats in dynamic locomotion in challenging unstructured terrain. However, in entertainment applications, the design and control of these robots face additional challenges in appealing to human audiences. This work aims to unify expressive, artist-directed motions and robust dynamic mobility for legged robots. To this end, we introduce a new bipedal robot, designed with a focus on character-driven mechanical features. We present a reinforcement learning-based control architecture to robustly execute artistic motions conditioned on command signals. During runtime, these command signals are generated by an animation engine which composes and blends between multiple animation sources. Finally, an intuitive operator interface enables real-time show performances with the robot. The complete system results in a believable robotic character, and paves the way for enhanced human-robot engagement in various contexts, in entertainment robotics and beyond.