VR-Based Haptic Simulator for Subsea Robot Teleoperations
VR-Based Haptic Simulator for Subsea Robot Teleoperations
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DOI：
10.1061/9780784483893.126
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发表时间：
2022-05
期刊：
影响因子：
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通讯作者：
Fang Xu;Qi Zhu;Shuai Li;Zhuoyuan Song;Jing Du
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文献类型：
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作者：
Fang Xu;Qi Zhu;Shuai Li;Zhuoyuan Song;Jing Du
海底工程作业严重依赖遥控潜水器（ROV），其性能取决于ROV与操作人员之间的无缝交互。由于海底环境的动态变化，如湍流的不确定性、能见度的影响以及对海底生态系统的干扰，海底ROV的控制对于从未接触过这种环境的人类操作员来说是一个挑战。即使进行了大量的练习，操作人员也很容易在海底作业中误判情况并做出错误的决定。本研究提出了一种基于混合现实系统（VR/AR）的直观人机协作方法。为了探索利用混合现实系统完成 ROV 控制的潜力，触觉套装与 VR 护目镜相结合，为操作员带来身临其境的海底环境。首先将全面的物理模型传输到 VR 设备，描绘详细的水下环境，包括湍流以及与周围物体的相互作用。然后触觉套装实时向操作者的身体执行相应的压力信号。来自触觉套装的反馈信号为操作员提供了机器人周围海底情况的真实感觉。这种身临其境的虚拟环境可确保 ROV 操作员实时了解邻近条件并预测变化。因此，训练较少的人类操作员可以根据他/她的直觉和经验来驾驶 ROV，以最大限度地提高性能并避免潜在的错误。
Subsea engineering operations heavily rely on remotely operated vehicles (ROV), and the performance depends on the seamless interaction between ROV and the human operator. Due to the dynamics of subsea environments such as the uncertainty of turbulence, affected visibility, and the interference with subsea ecosystems, control of subsea ROV is challenging for human operators who have never exposed to such an environment. Even with the tremendous amount of practice, the human operator can easily misjudge the situation and make wrong decisions in subsea operations. This research proposes an intuitive human-robot collaboration method based on mixed reality system (VR/AR). To explore the potentials of utilizing a mixed reality system to accomplish ROV control, a haptic suit is combined with VR goggles to bring an immersive subsea environment to the operator. A comprehensive physics model is first transferred to VR equipment, depicting a detailed underwater environment including turbulence and interaction with ambient objects. Then the haptic suit executes the corresponding pressure signals to the operator’s body in real-time. The feedback signals from haptic suit provide the human operator with realistic sensation of subsea situations peripheral to the robot. This immersive virtual environment ensures ROV operators of real-time awareness of the proximity conditions and prediction of changes. As a result, a less-trained human operator can pilot the ROV based on his/her intuition and experience to maximize the performance and avoid potential mistakes.