Details

Autor(en) / Beteiligte

• Xie, Zhaoming
• Tseng, Jonathan
• Starke, Sebastian
• van de Panne, Michiel
• Liu, C. Karen

Titel

Hierarchical Planning and Control for Box Loco-Manipulation

Ist Teil von

• Proceedings of the ACM on computer graphics and interactive techniques, 2023-08, Vol.6 (3), p.1-18, Article 31

Ort / Verlag

New York, NY, USA: ACM

Erscheinungsjahr

2023

Quelle

ACM Digital Library

Beschreibungen/Notizen

• Humans perform everyday tasks using a combination of locomotion and manipulation skills. Building a system that can handle both skills is essential to creating virtual humans. We present a physically-simulated human capable of solving box rearrangement tasks, which requires a combination of both skills. We propose a hierarchical control architecture, where each level solves the task at a different level of abstraction, and the result is a physics-based simulated virtual human capable of rearranging boxes in a cluttered environment. The control architecture integrates a planner, diffusion models, and physics-based motion imitation of sparse motion clips using deep reinforcement learning. Boxes can vary in size, weight, shape, and placement height. Code and trained control policies are provided.