Resilient, Provably-Correct, and High-Level Robot Behaviors
Resilient, Provably-Correct, and High-Level Robot Behaviors
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有弹性、可证明正确且高水平的机器人行为
DOI：
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发表时间：
2018
影响因子：
7.8
通讯作者：
H. Kress
中科院分区：
文献类型：
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作者：
K. W. Wong;Rüdiger Ehlers;H. Kress
无论机器人控制器是手动设计还是从高级任务规范合成，都需要对环境进行假设，这可能涉及对抗事件或合作机器人。在任何一种情况下，如果在运行时违反了这些假设，机器人将无法完成其任务，并可能会做一些意想不到的事情。在本文中，我们专注于从线性时序逻辑合成的控制器。我们解决的问题，使这些控制器对环境的假设违反机器人执行中常见的鲁棒性。我们的解决方案是一个三层的系统：首先，我们提出了一个离线的方法，占瞬态违规，使机器人仍然可以完成其任务后，暂时异常;第二层是一个在线的方法，自动放松的环境假设，以更好地捕捉环境行为，并允许机器人作出相应的反应;最后，在可能的情况下，通过与在工作空间中操作的环境机器人之一协商，我们自动修改实际的环境行为，使得另一个机器人满足我们的假设，并且两个机器人都完成它们的任务。
Whether robot controllers are manually designed or synthesized from high-level task specifications, assumptions about the environment need to be made, which can involve adversarial events or cooperative robots. In either case, if these assumptions are violated at runtime, the robot will fail to fulfill its task and will likely do something unexpected. In this paper, we focus on controllers synthesized from linear temporal logic. We tackle the problem of making these controllers robust against environment assumption violations that are common in robot execution. Our solution is a three-layer system: first, we propose an offline approach that accounts for transient violations such that the robot can still complete its task after temporary anomalies; the second layer is an online approach that automatically relaxes the environment assumptions to better capture environment behaviors and that allows the robot to react accordingly; and, finally, we automatically modify the actual environment behaviors, when possible, through negotiation with one of the environment robots operating in the workspace, such that our assumptions are met by the other robot and both robots accomplish their tasks.