Barrier Functions for Multiagent-POMDPs with DTL Specifications
Abstract
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.
Cite
@article{arxiv.2003.09267,
title = {Barrier Functions for Multiagent-POMDPs with DTL Specifications},
author = {Mohamadreza Ahmadi and Andrew Singletary and Joel W. Burdick and Aaron D. Ames},
journal= {arXiv preprint arXiv:2003.09267},
year = {2020}
}
Comments
arXiv admin note: text overlap with arXiv:1903.07823