This paper presents a complete and efficient coverage path planning method for mobile robots. Its applications include robots for de-mining, cleaning, painting and so on. When a mobile robot performs area coverage tas...
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ISBN:
(纸本)9781424408276
This paper presents a complete and efficient coverage path planning method for mobile robots. Its applications include robots for de-mining, cleaning, painting and so on. When a mobile robot performs area coverage task, completeness and efficiency of coverage are important factors. To achieve completeness easily, we adopt a divide and conquer strategy. We developed a novel cell decomposition algorithm that divides a given area into several cells. To achieve efficiency, each cell is covered by a robot motion that requires minimum time to cover the cell. The effectiveness of the method is verified using simulations.
The natural calamity or disaster may destroy all communication networks especially a cellular network that relies on a tower. Although many solutions to an ad hoc wireless network have been proposed, forming a network...
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The natural calamity or disaster may destroy all communication networks especially a cellular network that relies on a tower. Although many solutions to an ad hoc wireless network have been proposed, forming a network covering a respective region with mobile robots toward optimalcoverage remains to be an open problem. In this paper, we take the initiative to handle the optimal network coverage and path selection in disaster region with the help of multiple movable/rover robots. This paper consists of load balance distribution algorithm and optimal coverage algorithm applied to find the next optimally possible node location for all robots. Next, the robots maneuvering in an unknown disaster environment to identify the optimal path between the source and destination by using a particle swarm optimization algorithm. Finally, simulated results show that the algorithms can significantly improve the network coverage in the entire region, and the optimal path can effectively identify the optimal solution for all rover robots.
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