Frontier-based RTDP: A new approach to solving the robotic adversarial coverage problem

Roi Yehoshua, Noa Agmon, Gal A. Kaminka

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Area coverage is an important problem in robotics, where one or more robots axe required to visit all points in a given area. In this paper we consider a recently introduced version of the problem, adversarial coverage, in which the covering robot operates in an environment that contains threats that might stop it. The objective is to cover the target area as quickly as possible, while minimizing the probability that the robot will be stopped before completing the coverage. We first model this problem as a Markov Decision Process (MDP), and show that finding an optimal policy of the MDP also provides an optimal solution to this problem. Since the state space of the MDP is exponential in the size of the target area's map, we use real-time dynamic programming (RTDP), a well-known heuristic search algorithm for solving MDPs with large state spaces. Although RTDP achieves faster convergence than value iteration on this problem, practically it cannot handle maps with sizes larger them 7×7. Hence, we introduce the use of frontiers, states that separate the covered regions in the search space from those uncovered, into RTDP. Frontier-Based RTDP (FBRTDP) converges orders of magnitude faster than RTDP, and obtains significant improvement over the state-of-the-art solution for the adversarial coverage problem.

Original languageEnglish
Title of host publicationAAMAS 2015 - Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems
EditorsEdith Elkind, Gerhard Weiss, Pinar Yolum, Rafael H. Bordini
Pages861-869
Number of pages9
ISBN (Electronic)9781450337700
StatePublished - 2015
Event14th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2015 - Istanbul, Turkey
Duration: 4 May 20158 May 2015

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Volume2

Conference

Conference14th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2015
Country/TerritoryTurkey
CityIstanbul
Period4/05/158/05/15

Keywords

  • Adversarial coverage
  • Markov Decision Process
  • Mobile robot coverage
  • Motion and path planning
  • Real-time dynamic programming

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering

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