Design and Control of a Bipedal Robotic Character
This work addresses the problem of enhancing human-robot engagement in entertainment robotics, though it appears incremental as it builds on existing legged robot and reinforcement learning methods.
The paper tackled the challenge of unifying expressive, artist-directed motions with robust dynamic mobility for legged robots in entertainment, resulting in a believable robotic character system that enables real-time show performances.
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.