Data Sheet 1_Safety for mobile encountered-type haptic devices in large-scale virtual reality.pdf

Mobile robots are becoming more common in Virtual Reality applications, especially for delivering physical interactions through Encountered-Type Haptic Devices (ETHD). However, current safety standards and definitions of collaborative robots (Cobots) do not sufficiently address situations where an immersed user shares the workspace and interacts with a mobile robot without seeing it. In this paper, we explore the specific safety challenges of using mobile platforms for ETHDs in a large-scale immersive setup. We review existing robotic safety standards and perform a risk assessment of our immersive autonomous mobile ETHD system CoboDeck. We demonstrate a structured approach for potential risk identification and mitigation via a set of hardware and software safety measures. These include strategies for robot behavior, such as pre-emptive repositioning and active collision avoidance, as well as fallback mechanisms. We suggest a simulation-based testing framework that allows evaluating the safety measures systematically before involving human subjects. Based on that, we examine the impact of different proposed safety strategies on the number of collisions, robot movement, haptic feedback rendering, and noise resilience. Our results show considerably improved safety and robustness with our suggested approach.

移动机器人在虚拟现实（Virtual Reality）应用中的普及度日益提升，尤其适用于通过接触式触觉设备（Encountered-Type Haptic Devices, ETHD）实现实体交互的场景。然而，当前针对协作机器人（collaborative robots, Cobots）的安全标准与定义，并未充分覆盖沉浸式用户与移动机器人共享工作空间且无法直视机器人的交互场景。本文针对大规模沉浸式部署场景下为接触式触觉设备搭载移动平台的情况，探究其特有的安全挑战。我们梳理了现有机器人安全标准，并针对自研的沉浸式自主移动接触式触觉设备系统CoboDeck开展了风险评估。我们通过一系列硬件与软件安全措施，展示了一套用于潜在风险识别与缓解的结构化方案，其中包括机器人行为调控策略，例如前置重定位与主动避障，以及后备应急机制。我们提出了一种基于仿真的测试框架，可在开展人体受试者实验前，对安全措施进行系统性评估。基于该框架，我们分析了不同拟议安全策略对碰撞次数、机器人运动、触觉反馈渲染效果以及噪声鲁棒性的影响。实验结果表明，我们提出的方案可显著提升系统的安全性与鲁棒性。