arXiv:2607.06052cs.RO2026-07

构建首个融合人体动作与受力数据的仿人机器人交互评估基准

ThorArena: Benchmarking Humanoid Physical Interaction with Human Motion-Force Demonstrations

论文配图:ThorArena: Benchmarking Humanoid Physical Interaction with Human Motion-Force Demonstrations
图 1 · 摘自论文原文
  • 基于真人演示采集同步动作与受力数据,覆盖6类典型交互任务
  • 提出FATS评分体系,量化评估不同受力水平下的追踪精度与控制鲁棒性
  • 提供可复现的仿真回放协议,适合研究接触密集型机器人行为

仿人机器人需完成依赖物理交互的任务,但现有数据集和评估基准多聚焦运动学轨迹,忽略同步受力信息。本文提出ThorArena,基于真实人类示范,采集六类典型交互任务中全身动作与双手受力数据。在此基础上,设计力感知评估指标,包括力感知追踪分数(FATS)及配套诊断指标,综合评估全身体追踪精度、不同受力水平下的鲁棒性、控制努力程度与任务存活率。建立统一仿真回放协议,在模拟环境中重现记录的交互力,并提供标准化评估接口。在多个全身体控制策略上的实验表明,力感知评估揭示了传统无受力评估中隐藏的显著性能差异。ThorArena为研究力感知交互提供了可复现的框架,是接触密集型仿人机器人行为的新基准。

原文摘要 · Abstract (English)

Humanoid robots are increasingly expected to perform contact-rich tasks that require not only accurate whole-body motion but also robust physical interaction with surrounding objects and humans. Although recent advances in humanoid motion imitation and whole-body control have achieved remarkable tracking performance, existing datasets and benchmarks primarily focus on kinematic motion while largely overlooking synchronized interaction forces. As a result, current evaluations fail to capture how external interaction forces affect tracking accuracy, stability, and control robustness. In this paper, we present ThorArena, a benchmark for evaluating force-aware humanoid interaction based on human demonstrations with synchronized motion and force measurements. We collect a real-world interaction dataset that simultaneously captures whole-body human motion and forces exerted by both hands across six representative physical interaction tasks. Based on these demonstrations, we propose force-aware evaluation metrics that jointly assess whole-body tracking accuracy, robustness under different force levels, control effort, and episode survival through the Force-Aware Tracking Score (FATS) and complementary diagnostic metrics. We further establish a unified benchmark protocol that replays recorded interaction forces in simulation and provides a standardized evaluation interface for different humanoid control policies. Experiments on representative whole-body control policies demonstrate that force-aware evaluation reveals substantial performance differences that remain largely hidden under conventional no-force evaluation. ThorArena provides a practical and reproducible framework for studying force-aware humanoid interaction and offers a new benchmark for evaluating contact-rich humanoid behaviors.

仿人机器人力感知交互评估基准测试

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