外观
论文arXiv 2605.313431 个月前
面向感知式腿式移动操作的地形感知全身控制学习
原文链接：Learning Terrain-Aware Whole-Body Control for Perceptive Legged Loco-Manipulation（arXiv 2605.31343 · 发布日期：2026-09-18）
Learning Terrain-Aware Whole-Body Control for Perceptive Legged Loco-Manipulation
针对全身控制缺乏地形外感知的问题，提出TA-WBC强化学习统一策略，并在仿真和真实实验中验证。
核心要点
- 腿式操作机器人需协调腿臂扩展工作空间，但现有全身控制多依赖本体感知，难适应复杂地形。
- TA-WBC采用面向全身移动操作的强化学习统一策略，并用层次外感知编码器提取地形特征。
- 基于足端接触平面采样末端目标，解耦操作目标与机身高度、横滚和俯仰变化。
- 仿真与真实实验显示控制器更鲁棒，可带来更大可达空间、更小跟踪误差和更少意外绊 stumble。
验证范围与局限：验证范围为仿真和真实世界的复杂地形移动操作实验，摘要未说明具体任务或机器人数量。
英文摘要 (Abstract)
Legged manipulators integrate exceptional terrain adaptability along with mobile manipulation capabilities, which make them highly promising for deployment in human-centric environments. By coordinating the control of both legs and arms, a whole-body controller can significantly expand the operational workspace of legged manipulators. However, many existing whole-body controllers primarily depend on proprioception and do not incorporate the critical exteroception required for effective terrain topology perception. This limitation can hinder their ability to adapt to varying environmental conditions and navigate complex terrains effectively. In this paper, we introduce TA-WBC, a terrain-aware whole-body control framework for legged manipulators, which features a novel RL-based unified policy tailored to whole-body loco-manipulation tasks in various terrains. Specifically, we employ a \rev{hierarchical exteroceptive encoder} to extract terrain features, providing an essential basis for the robot to proactively adapt posture and footholds. Furthermore, to facilitate stable cross-terrain loco-manipulation, we propose a novel end-effector sampling method based on the foot contact plane, \rev{decoupling the manipulation target from base height, roll, and pitch variations}. Moreover, a dual-policy distillation module is introduced to integrate expansive whole-body motion with terrain adaptability without catastrophic forgetting. The simulation and real-world experiments validate the robustness of our proposed controller, which leads to a larger reachable space, less tracking error, and reduced unexpected stumbles. This unified policy highlights the promising capabilities of legged manipulators in performing loco-manipulation tasks across complex terrains.
作者：Sikai Guo, Yudong Zhong, Guoyang Zhao, Botao Dang, Zhihai Bi, Jun Ma
来源
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