Pattern-Based Genetic Algorithm Approach to Coverage Path Planning for Mobile Robots
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- Kapanoglu M., Ozkan M., Yazıcı A., Parlaktuna O. (2009) Pattern-Based Genetic Algorithm Approach to Coverage Path Planning for Mobile Robots. In: Allen G., Nabrzyski J., Seidel E., van Albada G.D., Dongarra J., Sloot P.M.A. (eds) Computational Science – ICCS 2009. ICCS 2009. Lecture Notes in Computer Science, vol 5544. Springer, Berlin, Heidelberg
Sensor-based mobile robot coverage path planning (MRCPP) problem is a challenging problem in robotic management. We here develop a genetic algorithm (GA) for MRCPP problems. The area subject to coverage is modeled with disks representing the range of sensing devices. Then the problem is defined as finding a path which runs through the center of each disk at least once with minimal cost of full coverage. The proposed GA utilizes prioritized neighborhood-disk information to generate practical and high-quality paths for the mobile robot. Prioritized movement patterns are designed to generate efficient rectilinear coverage paths with no narrow-angle turn; they enable GA to find optimal or near-optimal solutions. The results of GA are compared with a well-known approach called backtracking spiral algorithm (BSA). Experiments are also carried out using P3-DX mobile robots in the laboratory environment.
KeywordsGenetic algorithms Coverage path planning Mobile robot
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