Telemanipulation in power stations commonly require robots first to open doors and then gain access to a new workspace. However, the opened doors can easily close by disturbances, interrupt the operations, and potentially lead to collision damages. Although existing telemanipulation is a highly efficient master–slave work pattern due to human-in-the-loop control, it is not trivial for a user to specify the optimal measures to guarantee safety. This paper investigates the safety-critical motion planning and control problem to balance robotic safety against manipulation performance during work emergencies. Based on a dynamic workspace released by door-closing, the interactions between the workspace and robot are analyzed using a partially observable Markov decision process, thereby making the balance mechanism executed as belief tree planning. To act the planning, apart from telemanipulation actions, we clarify other three safety-guaranteed actions: on guard, defense and escape for self-protection by estimating collision risk levels to trigger them. Besides, our experiments show that the proposed method is capable of determining multiple solutions for balancing robotic safety and work efficiency during telemanipulation tasks.

电站中的远程操作通常需要机器人先开门，然后才能进入新的工作空间。然而，打开的门很容易被干扰关闭，中断操作，并可能导致碰撞损坏。尽管由于人在环控制，现有的远程操作是一种高效的主从工作模式，但用户指定最佳措施以保证安全并非易事。本文研究了安全关键的运动规划和控制问题，以在工作紧急情况下平衡机器人安全与操作性能。基于关门释放的动态工作空间，使用部分可观察的马尔可夫决策过程分析工作空间和机器人之间的相互作用，从而使平衡机制执行为信念树规划。为了执行计划，除了遥控操作之外，我们通过估计碰撞风险水平来触发其他三个安全保证动作：警戒、防御和逃生以进行自我保护。此外，我们的实验表明，所提出的方法能够确定多种解决方案，以在远程操作任务期间平衡机器人的安全性和工作效率。