无需访问底层控制，实现跨机器人实时远程操作
UTTG_ A Universal Teleoperation Approach via Online Trajectory Generation
- 通过URDF自动提取参数，统一接口支持多机器人部署
- 在线生成连续轨迹，解决人机控制频率不匹配问题
- 支持高精度与快速模式，适合不同任务需求
远程操作在危险环境作业中至关重要，也是机器人学习中获取专家示范的关键手段。现有方法普遍存在对硬件依赖强、人机控制频率不匹配的问题。本文提出一种通用远程操作框架，能自动从统一机器人描述格式（URDF）文件中提取运动学参数，并通过统一接口实现跨多种机器人的即插即用部署。提出的插值算法通过在线连续轨迹生成，弥合低频人类输入与高频机器人控制命令之间的频率差距，且无需访问封闭的底层控制回路。为提升轨迹平滑性，引入最小拉伸样条优化运动质量。系统提供高精度与快速两种模式，适配不同任务需求。在包括双臂机器人在内的多种机器人平台上实验验证了方法的通用性与平稳性。代码基于C++开发，提供Python接口，开源地址：https://github.com/IRMV-Manipulation-Group/UTTG。
原文摘要 · Abstract (English)
Teleoperation is crucial for hazardous environment operations and serves as a key tool for collecting expert demonstrations in robot learning. However, existing methods face robotic hardware dependency and control frequency mismatches between teleoperation devices and robotic platforms. Our approach automatically extracts kinematic parameters from unified robot description format (URDF) files, and enables pluggable deployment across diverse robots through uniform interfaces. The proposed interpolation algorithm bridges the frequency gap between low-rate human inputs and high-frequency robotic control commands through online continuous trajectory generation, \n{while requiring no access to the closed, bottom-level control loop}. To enhance trajectory smoothness, we introduce a minimum-stretch spline that optimizes the motion quality. The system further provides precision and rapid modes to accommodate different task requirements. Experiments across various robotic platforms including dual-arm ones demonstrate generality and smooth operation performance of our methods. The code is developed in C++ with python interface, and available at https://github.com/IRMV-Manipulation-Group/UTTG.
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