CoboDeck: A Large-Scale Haptic VR System Using a Collaborative Mobile Robot

Soroosh Mortezapoor, Khrystyna Vasylevska, Emanuel Vonach, H. Kaufmann
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引用次数: 1

Abstract

We present CoboDeck - our proof-of-concept immersive virtual reality haptic system with free walking support. It provides prop-based encountered-type haptic feedback with a mobile robotic platform. Intended for use as a design tool for architects, it enables the user to directly and intuitively interact with virtual objects like walls, doors, or furniture. A collaborative robotic arm mounted on an omnidirectional mobile platform can present a physical prop that matches the position and orientation of a virtual counterpart anywhere in large virtual and real environments. We describe the concept, hardware, and software architecture of our system. Furthermore, we present the first behavioral algorithm tailored for the unique challenges of safe human-robot haptic interaction in VR, explicitly targeting availability and safety while the user is unaware of the robot and can change trajectory at any time. We explain our high-level state machine that controls the robot to follow a user closely and rapidly escape from him as required by the situation. We present our technical evaluation. The results suggest that our chasing approach saves time, decreases the travel distance and thus battery usage, compared to more traditional approaches for mobile platforms assuming a fixed parking position between interactions. We also show that the robot can escape from the user and prevent a possible collision within a mean time of 1.62 s. Finally, we confirm the validity of our approach in a practical validation and discuss the potential of the proposed system.
CoboDeck:使用协作移动机器人的大规模触觉VR系统
我们提出CoboDeck -我们的概念验证沉浸式虚拟现实触觉系统与自由行走的支持。它通过移动机器人平台提供基于道具的遭遇式触觉反馈。作为建筑师的设计工具,它使用户能够直接直观地与虚拟对象(如墙壁,门或家具)进行交互。安装在全向移动平台上的协作机械臂可以在大型虚拟和真实环境的任何地方呈现与虚拟对手的位置和方向相匹配的物理支柱。我们描述了系统的概念、硬件和软件架构。此外,我们提出了第一个针对VR中安全人机触觉交互的独特挑战量身定制的行为算法,明确针对用户不知道机器人的可用性和安全性,并且可以随时改变轨迹。我们解释了我们的高级状态机,它控制机器人紧跟用户,并根据情况的需要迅速逃离用户。我们提出我们的技术评估。结果表明,与传统的移动平台方法相比,我们的追赶方法节省了时间,减少了行驶距离,从而减少了电池的使用,而传统的移动平台方法在交互之间假设了固定的停车位置。我们还表明,机器人可以在平均1.62秒内逃离用户并防止可能的碰撞。最后,我们在实际验证中验证了我们方法的有效性,并讨论了所提出系统的潜力。
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