论文标题
具有DTL规格的多型POMDP的障碍功能
Barrier Functions for Multiagent-POMDPs with DTL Specifications
论文作者
论文摘要
多代理的部分可观察到的马尔可夫决策过程（MPOMDPS）提供了一个框架，以代表不确定性和部分观察的异质自治药物。在本文中，鉴于人类操作员或常规计划方法提供的名义政策，我们提出了一种基于障碍功能的技术，以设计最小干扰的安全屏幕，以确保在线性分布时间逻辑（LDTL）方面确保高级规格满意。为此，我们使用足够和必要的条件来基于离散时间屏障功能（DTBF）的给定集合，并为有限时间DTBF制定足够的条件来研究有限的时间收敛到集合。然后，我们证明可以将不同的LDTL任务/安全规范作为一组不变性或有限的时间到达问题。我们证明，可以通过一系列单步贪婪算法在线实施提出的安全屏合成方法。我们使用涉及机器人团队的实验证明了提出方法的功效。
Multi-agent partially observable Markov decision processes (MPOMDPs) provide a framework to represent heterogeneous autonomous agents subject to uncertainty and partial observation. In this paper, given a nominal policy provided by a human operator or a conventional planning method, we propose a technique based on barrier functions to design a minimally interfering safety-shield ensuring satisfaction of high-level specifications in terms of linear distribution temporal logic (LDTL). To this end, we use sufficient and necessary conditions for the invariance of a given set based on discrete-time barrier functions (DTBFs) and formulate sufficient conditions for finite time DTBF to study finite time convergence to a set. We then show that different LDTL mission/safety specifications can be cast as a set of invariance or finite time reachability problems. We demonstrate that the proposed method for safety-shield synthesis can be implemented online by a sequence of one-step greedy algorithms. We demonstrate the efficacy of the proposed method using experiments involving a team of robots.
