让机器人移动、抓取、视觉协同更自然，提升操作成功率与效率。
EHC-MM: Embodied Holistic Control for Mobile Manipulation
- 将移动与抓取的协调问题建模为二次规划，用sig(w)动态调节关注重点。
- 真实场景下任务成功率95.6%，时间效率提升52.8%。
- 适合需要多模态协同控制的移动机械臂应用，如仓储搬运。
移动操作通常涉及移动底盘、机械臂和摄像头分别负责移动、精准操作与感知。远端移动、近端抓取（DMCG）原则对整体控制至关重要。本文提出面向移动操作的具身整体控制（EHC-MM），引入具身函数sig(w)，将DMCG原则形式化为二次规划（QP）问题，使机器人根据自身状态与环境动态平衡移动与操作的优先级。同时提出基于监控位置的伺服控制（MPBS）与sig(w）结合，实现操作中对目标的持续追踪。该方法实现了底盘、机械臂与摄像头的协同控制，显著提升任务效率。通过大量仿真与真实实验验证，本方法在真实场景中达到95.6%的成功率，并实现52.8%的时间效率提升。
原文摘要 · Abstract (English)
Mobile manipulation typically entails the base for mobility, the arm for accurate manipulation, and the camera for perception. The principle of Distant Mobility, Close Grasping(DMCG) is essential for holistic control. We propose Embodied Holistic Control for Mobile Manipulation(EHC-MM) with the embodied function of sig(w): By formulating the DMCG principle as a Quadratic Programming (QP) problem, sig(w) dynamically balances the robot's emphasis between movement and manipulation with the consideration of the robot's state and environment. In addition, we propose the Monitor-Position-Based Servoing (MPBS) with sig(w), enabling the tracking of the target during the operation. This approach enables coordinated control among the robot's base, arm, and camera, enhancing task efficiency. Through extensive simulations and real-world experiments, our approach significantly improves both the success rate and efficiency of mobile manipulation tasks, achieving a 95.6% success rate in real-world scenarios and a 52.8% increase in time efficiency.
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