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Distributed Coverage Estimation and Control for Multirobot Persistent Tasks

delete2016-12-01
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PRE
AI
J
José Manuel Palacios-Gasós *
E
Eduardo Montijano
C
Carlos Sagüés
S
Sergio Llorente
DOI:10.1109/TRO.2016.2602383delete
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Abstract

Abstract

En 中文
In this paper, we address the problem of persistently covering an environment with a group of mobile robots. In contrast to traditional coverage, in our scenario the coverage level of the environment is always changing. For this reason, the robots have to continually move to maintain a desired coverage level. In this context, our contribution is a complete approach to the problem, including distributed estimation of the coverage and control of the motion of the robots. First, we present an algorithm that allows every robot to estimate the global coverage function only with local information. We pay special attention to the characterization of the algorithm, establishing bounds on the estimation error, and we demonstrate that the algorithm guarantees a perfect estimation in particular areas. Second, we introduce a new function to determine the possible improvement of the coverage at each point of the environment. Upon this metric, we build a motion control strategy that drives the robots to the points of the highest improvement while following the direction of the gradient of the function. Finally, we simulate the proposal to test its correctness and performance.
Keywords:
Distributed systems
multi-robot systems
persistent coverage
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Journal

IEEE Transactions on Robotics cover
IEEE Transactions on Robotics
IF:
10.5
Papers:
3.3K
Citations:
2.8W

Organization

U
University of Zaragoza
Scholars:
1.5W
Papers: 1.2W
Citations: 14