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.

翻译：人类通过结合移动操作技能完成日常任务。构建能够同时处理这两种技能的系统对于创建虚拟人类至关重要。本文提出一种可解决箱体重排任务的物理仿真人体模型，该任务需要同时运用移动与操作技能。我们提出一种分层控制架构，其中每个层级在不同抽象层次上解决问题，最终实现基于物理仿真的虚拟人类在杂乱环境中重新排列箱体的能力。该控制架构集成了规划器、扩散模型以及基于深度强化学习对稀疏运动片段进行物理仿真的运动模仿技术。箱体的尺寸、重量、形状及放置高度均可变化。本文同时提供了代码与训练好的控制策略。