Sensor selection for detecting deviations from a planned itinerary
Sensor selection for detecting deviations from a planned itinerary
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DOI：
10.1109/iros51168.2021.9636582
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发表时间：
2021-03
期刊：
影响因子：
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通讯作者：
Hazhar Rahmani;Dylan A. Shell;J. O’Kane
中科院分区：
文献类型：
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作者：
Hazhar Rahmani;Dylan A. Shell;J. O’Kane
假设一个智能体断言它将以某种方式在环境中移动。当代理人执行其动议时，如何验证其主张？这个问题出现在一系列的背景下，包括验证有关机器人行为的安全声明，安全和监控的应用，以及科学实验的概念和（物理）设计和物流。给定一组可行的传感器进行选择，我们问如何选择传感器最优，以确保代理的执行确实适合其预先披露的行程。我们的治疗是区别于以前的工作在传感器选择两个方面：行程的形式（一个经常性的语言的过渡）和家庭的传感器选择可以被分组为一个单一的选择。两者紧密联系在一起，允许构建产品自动机，因为相同的物理传感器（即，相同的选择）可以出现多次。本文建立了硬度的传感器选择行程验证在此治疗，并提出了一个精确的算法，基于整数线性规划（ILP）制定，能够解决问题的情况下，中等大小。我们证明了其有效性的小规模的案例研究，包括一个动机的野生动物跟踪。
Suppose an agent asserts that it will move through an environment in some way. When the agent executes its motion, how does one verify the claim? The problem arises in a range of contexts including validating safety claims about robot behavior, applications in security and surveillance, and for both the conception and the (physical) design and logistics of scientific experiments. Given a set of feasible sensors to select from, we ask how to choose sensors optimally in order to ensure that the agent’s execution does indeed fit its pre-disclosed itinerary. Our treatment is distinguished from prior work in sensor selection by two aspects: the form the itinerary takes (a regular language of transitions) and that families of sensor choices can be grouped as a single choice. Both are intimately tied together, permitting construction of a product automaton because the same physical sensors (i.e., the same choice) can appear multiple times. This paper establishes the hardness of sensor selection for itinerary validation within this treatment, and proposes an exact algorithm based on an integer linear programming (ILP) formulation that is capable of solving problem instances of moderate size. We demonstrate its efficacy on small-scale case studies, including one motivated by wildlife tracking.