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Main Authors: Grandia, Ruben, Knoop, Espen, Hopkins, Michael A., Wiedebach, Georg, Bishop, Jared, Pickles, Steven, Müller, David, Bächer, Moritz
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2501.05204
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author Grandia, Ruben
Knoop, Espen
Hopkins, Michael A.
Wiedebach, Georg
Bishop, Jared
Pickles, Steven
Müller, David
Bächer, Moritz
author_facet Grandia, Ruben
Knoop, Espen
Hopkins, Michael A.
Wiedebach, Georg
Bishop, Jared
Pickles, Steven
Müller, David
Bächer, Moritz
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2501_05204
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Design and Control of a Bipedal Robotic Character
Grandia, Ruben
Knoop, Espen
Hopkins, Michael A.
Wiedebach, Georg
Bishop, Jared
Pickles, Steven
Müller, David
Bächer, Moritz
Robotics
Machine Learning
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.
title Design and Control of a Bipedal Robotic Character
topic Robotics
Machine Learning
url https://arxiv.org/abs/2501.05204