The Capacitated Arc Routing Problem: Valid Inequalities and Facets
Computational Optimization and Applications
Approximation algorithms for lawn mowing and milling
Computational Geometry: Theory and Applications
Introduction to AI Robotics
Coverage for robotics – A survey of recent results
Annals of Mathematics and Artificial Intelligence
A Short History of Cleaning Robots
Autonomous Robots
A cutting plane algorithm for the capacitated arc routing problem
Computers and Operations Research
Improvement Procedures for the Undirected Rural Postman Problem
INFORMS Journal on Computing
A Tabu Search Heuristic for the Capacitated Arc Routing Problem
Operations Research
A Hierarchical Relaxations Lower Bound for the Capacitated Arc Routing Problem
HICSS '02 Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS'02)-Volume 3 - Volume 3
New lower bound for the capacitated arc routing problem
Computers and Operations Research
Sensor-based coverage with extended range detectors
IEEE Transactions on Robotics
Deployment of mobile robots with energy and timing constraints
IEEE Transactions on Robotics
Capacitated arc routing problem with deadheading demands
Computers and Operations Research
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Multi-robot sensor-based coverage path planning requires every point given in the workspace has to be covered at least by a sensor of a robot in the robot team. In this study, a novel algorithm was proposed for the sensor-based coverage of narrow environments by considering energy capacities of the robots. For this purpose, the environment was modeled by a Generalized Voronoi diagram-based graph to guarantee complete sensor-based coverage. Then, depending on the required arc set, a complete coverage route was created by using the Chinese Postman Problem or the Rural Postman Problem, and this route was partitioned among robots by considering energy capacities. Route partitioning was realized by modifying the Ulusoy partitioning algorithm which has polynomial complexity. This modification handles two different energy consumptions of mobile robots during sensor-based coverage, which was not considered before. The developed algorithm was coded in C++ and implemented on P3-DX mobile robots both in laboratory and in MobileSim simulation environments. It was shown that the convenient routes for energy constrained multi-robots could be generated by using the proposed algorithm in less than 1 s.