# 人形机器人全身控制中的精确 SE(3) 末端执行器跟踪

> 原文链接：https://robotics.hellobike.com/papers/2026-10-07-2610-09479
> 频道：papers | 更新日期：2026-10-07 | 标签：arxiv, cs.RO
> 核心摘要：针对人形全身运动中的末端位姿精确跟踪，ResGAC结合几何导纳控制与残差强化学习，并在真实Unitree G1上验证。

# 人形机器人全身控制中的精确 SE(3) 末端执行器跟踪

::: v-pre
> 原文链接：[Precise SE(3) End-Effector Tracking in Whole-Body Humanoid Control](https://arxiv.org/abs/2610.09479)（arXiv 2610.09479 · 发布日期：2026-10-07）

**Precise SE(3) End-Effector Tracking in Whole-Body Humanoid Control**

针对人形全身运动中的末端位姿精确跟踪，ResGAC结合几何导纳控制与残差强化学习，并在真实Unitree G1上验证。

## 核心要点

- 全身运动中的浮基振荡、重力、动态耦合和行走扰动使末端精确跟踪困难。
- GAC提供结构化SE任务空间反馈和名义手臂关节目标，残差RL补偿未建模动力学并协调运动平衡。
- 左不变几何形式支持跨参考系复用控制律，地面附着航向框架减少行走引起的参考扰动。
- 在四个站立跟踪基准中优于SONIC等基线，插孔任务成功率90%；视频见补充材料和项目网站。

**验证范围与局限**：验证范围包括真实Unitree G1上的四个站立末端跟踪基准、站立插孔任务和下肢运动中的世界坐标系SE位姿跟踪。

## 英文摘要 (Abstract)

Precise end-effector tracking during humanoid whole-body motion is challenging due to floating-base oscillations, gravity, dynamic coupling, and locomotion-induced disturbances. We propose ResGAC, a whole-body humanoid controller for precise end-effector pose tracking that combines geometric admittance control (GAC) with residual reinforcement learning. GAC provides structured $\SE$ task-space feedback and generates nominal arm joint-position targets, while residual RL compensates for unmodeled dynamics and coordinates locomotion and balance in the shared joint-position action space. The left-invariant geometric formulation allows the same GAC law to be used across manipulation reference frames. This enables the use of a ground-attached heading frame that preserves planar locomotion while removing pelvis roll, pitch, and heave from the manipulation reference, thereby reducing reference-induced end-effector motion during locomotion. ResGAC is validated on a real Unitree G1 humanoid. Across four standing end-effector tracking benchmarks, ResGAC consistently outperforms representative baselines, including SONIC, achieving lower translational and rotational errors. Real-world experiments further demonstrate reduced propagation of pelvis motion to the desired end-effector pose using the proposed ground-attached heading frame. ResGAC achieves $90\%$ success in a standing peg-in-hole task compared with $50\%$ for SONIC, and accurate world-frame $\SE$ end-effector pose tracking during lower-body motion. Experimental videos are included in the supplementary material and are also available on the project website: https://resgac.github.io/ResGAC-website/.

作者：Joohwan Seo, Xiaofeng Guo, Jinkun Cao, Roberto Horowitz, Rocky Duan, Guanya Shi, Koushil Sreenath
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## 原始参考来源 (Sources)

- [arXiv 2610.09479：Precise SE(3) End-Effector Tracking in Whole-Body Humanoid Control](https://arxiv.org/abs/2610.09479)