NEXUS：面向地形自适应遥操作的全感知全身控制
NEXUS: Perceptive Whole-Body Control for Terrain-Adaptive Teleoperation
- The Institute of Artificial Intelligence, China Telecom (TeleAI)（中国电信人工智能研究院（TeleAI））
- Shanghai Jiao Tong University（上海交通大学）
- The University of Hong Kong（香港大学）
- Zhejiang University（浙江大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
NEXUS提出一种结合人类动作指令与机载感知反馈的全身控制框架，通过可扩展算法生成近千小时配对动作数据并训练教师-学生控制器，实现跨地形遥操作，在基准测试和真实部署中优于现有方法。
AI中文摘要：
全身遥操作要求人形机器人在操作者与自身所处地形不同时，仍能复现操作者的行为。这要求机器人感知局部地形并相应地调整姿态和接触，而非逐帧复制操作者的动作。然而，将同一行为在平坦地面和不同地形之间关联起来的配对动作数据仍然稀缺，限制了用于学习地形自适应控制的监督信号。为实现在不匹配地形间的全身遥操作，我们提出了NEXUS，一种结合人类动作指令与机载感知反馈的全感知全身控制框架。我们首先开发了一种可扩展的地形感知自适应算法，该算法能够高效地生成跨动作和地形的优质动作对，无需针对每个动作或地形进行调参。利用总计近1,000小时的配对动作语料库，我们通过教师-学生学习训练了一个全感知全身控制器，以在各种地形上复现指令行为。实验表明，该方法能高效、可扩展地生成高质量动作数据，并显示NEXUS兼具广泛的行为覆盖、地形适应性和跟踪保真度，在评估基准上优于现有全身控制器。零样本的真实世界部署实现了在多种未见地形上的实时全身遥操作，进一步验证了我们方法的泛化能力。项目网站：此https URL
英文摘要：
Whole-body teleoperation requires a humanoid robot to reproduce a human operator's behavior even when their terrains differ. This demands that the robot perceive local terrain and adapt its posture and contacts accordingly, rather than copy the operator's motion frame by frame. However, paired motion data linking the same behaviors across flat ground and different terrains remain scarce, limiting supervision for learning terrain-adaptive control. To enable whole-body teleoperation across mismatched terrains, we introduce NEXUS, a perceptive whole-body control framework that combines human motion commands with onboard sensory feedback. We first develop a scalable terrain-aware adaptation algorithm that efficiently generates high-quality motion pairs across motions and terrains without per-motion or per-terrain tuning. Using a paired motion corpus totaling nearly 1,000 hours, we train a perceptive whole-body controller through teacher-student learning to reproduce commanded behaviors across terrains. Experiments demonstrate efficient, scalable generation of high-quality motion data and show that NEXUS combines broad behavioral coverage with terrain adaptability and tracking fidelity, outperforming existing whole-body controllers on the evaluated benchmarks. Zero-shot real-world deployment enables real-time whole-body teleoperation on diverse unseen terrains, further validating the generalization of our method. Project website: https://nexus-humanoid.github.io/
