外观
论文arXiv 2610.1488918 天前
LETS：用于力反馈双边遥操作的低开销外部扭矩感知
原文链接：LETS: Low-Overhead External-Torque Sensing for Force-Feedback Bilateral Teleoperation（arXiv 2610.14889 · 发布日期：2026-10-10）
LETS: Low-Overhead External-Torque Sensing for Force-Feedback Bilateral Teleoperation
LETS针对双边遥操作外部扭矩估计问题，用物理引导学习降低传感器依赖，并在自由空间和接触遥操作中验证稳定力反馈。
核心要点
- 商用机械臂的厂家扰动扭矩估计常不准确，末端力/扭矩传感器会增加成本和负载。
- LETS将刚体动力学交给递归牛顿-欧拉逆动力学，仅学习机器人特定残差。
- 方法只用URDF模型和关节反馈，排除控制命令，使估计与控制命令输入解耦。
- 用12分钟自由运动数据训练且少于一分钟；自由空间和接触误差分别低于厂家估计69%和28%。
验证范围与局限：验证范围为双边遥操作中的自由空间与接触场景，摘要未说明机器人数量。
英文摘要 (Abstract)
Bilateral teleoperation with force feedback is becoming increasingly important, and the quality of external-torque estimation is critical to this process. However, manufacturer-provided disturbance-torque estimates on commercial robotic arms are often inaccurate, while the use of end-effector force/torque sensors adds cost and payload. We propose LETS, a physics-guided learning approach that assigns rigid-body dynamics to recursive Newton-Euler inverse dynamics and reserves learning for only the robot-specific residual. LETS uses only the robot's URDF model and joint feedback, deliberately excluding control commands and thereby decoupling external-torque estimation from control-command inputs. It trains on 12 minutes of free-motion data in under one minute, without requiring a dedicated end-effector six-axis force/torque sensor. In bilateral teleoperation, LETS achieves real-time external-torque estimation that enables stable force feedback. Its free-space error is 69% lower than the manufacturer-provided estimate, substantially reducing coupled oscillations between leader and follower; its contact error is 28% lower, yielding more accurate haptic feedback.
作者：Zonghao Guo, Dongchen Guan, Yubo Wang, Peng Yang
来源
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