实时虚拟现实遥控机械臂，能自动避障并低延迟响应。
A study on a Real-Time VR-Based Teleoperation Framework for Manipulator in Dynamic Environment
- 在VR界面中融合GPU加速逆运动学与轨迹优化，每帧生成合规动作
- 7自由度机械臂实验显示三类场景下均稳定运行且主动避障
- 适合需要高安全性和低延迟的工业远程操作场景
机器人遥操作可在危险环境中实现安全、非接触的任务执行，随着近期虚拟现实技术的发展，其应用范围不断扩大。然而，许多现有的VR遥操作研究主要作为机器人模仿学习的数据采集工具，通常未明确处理动态障碍物、工作空间变化或碰撞风险。为确保操作员安全，实际部署中的遥操作必须具备低延迟反应能力，并对新手操作失误具有鲁棒性。本文提出一种基于虚拟现实的实时遥操作框架，支持在动态环境中进行机械臂实时操控，可同时应对静态和移动障碍物的碰撞。该框架在VR界面中集成了GPU加速的逆运动学求解与轨迹优化算法，在每个控制周期内根据机器人约束生成可行的关节指令。使用7自由度机械臂在三种场景下进行实验：无障碍、静态障碍与移动障碍环境。结果表明，该方法在保持操作者意图的同时，能在障碍物干扰时生成安全绕行路径，展现出稳定的在线行为与良好的碰撞感知能力。
原文摘要 · Abstract (English)
Robot teleoperation enables safe, non-contact task execution in hazardous environments where direct human access is difficult, and its application has expanded with recent VR technologies. Many VR teleoperation studies, however, have primarily served as data-collection tools for robot imitation learning, so they often do not explicitly address dynamic obstacles, workspace changes, or collision risks during operation. For real deployment aimed at operator safety, teleoperation must react to dynamic situations with low latency and remain robust to mistakes made by inexperienced operators. This paper presents a VR teleoperation framework that supports real-time manipulation while handling collisions with both static and moving obstacles. The framework integrates GPU-accelerated inverse kinematics and trajectory optimization within a VR interface to generate feasible joint commands at each control cycle under robot constraints. Experiments with a 7-DoF manipulator demonstrate stable online behavior and collision-aware motion generation across three scenarios: obstacle-free, static-obstacle, and moving-obstacle environments. The results indicate that the proposed approach generates motion consistent with the operator's command while producing safe detours when obstacles interfere with the commanded path.
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