Integrated real-time task and motion planning for multiple robots under path and communication uncertainties

We consider a problem where robots are given a set of task locations to visit with coarsely known distances. The robots must find the task ordering that reduces the overall distance to visit the tasks. We propose an abstraction that models the uncertainty in the paths, and a Markov Decision Process-...

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Bibliographic Details
Published inRobotica Vol. 36; no. 3; pp. 353 - 373
Main Authors Woosley, Bradley, Dasgupta, Prithviraj
Format Journal Article
LanguageEnglish
Published Cambridge, UK Cambridge University Press 01.03.2018
Subjects
Algorithms
Computer simulation
Coordination
Markov analysis
Markov chains
Motion planning
Multiple robots
Robot dynamics
Robots
Uncertainty
Exploration
Path uncertainty
Multi-robot
Real time
Simultaneous task and motion planning
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Summary:We consider a problem where robots are given a set of task locations to visit with coarsely known distances. The robots must find the task ordering that reduces the overall distance to visit the tasks. We propose an abstraction that models the uncertainty in the paths, and a Markov Decision Process-based algorithm that selects paths that reduces the expected distance to visit the tasks. We also describe a distributed coordination algorithm to resolve path conflicts. We have shown that our task selection is optimal, our coordination is deadlock-free, and have experimentally verified our approach in hardware and simulation.
ISSN:0263-5747
1469-8668
DOI:10.1017/S0263574717000443