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Open AccessArticle

Path Planning of Mobile Robots Based on a Multi-Population Migration Genetic Algorithm

1
School of Computer and Information Engineering, Tianjin Chengjian University, Tianjin 300384, China
2
School of International Education, Tianjin Chengjian University, Tianjin 300384, China
3
Tianjin Keyvia Electric Co., Ltd, Tianjin 300384, China
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(20), 5873; https://doi.org/10.3390/s20205873
Received: 3 October 2020 / Revised: 14 October 2020 / Accepted: 15 October 2020 / Published: 17 October 2020
(This article belongs to the Section Sensors and Robotics)
In the field of robot path planning, aiming at the problems of the standard genetic algorithm, such as premature maturity, low convergence path quality, poor population diversity, and difficulty in breaking the local optimal solution, this paper proposes a multi-population migration genetic algorithm. The multi-population migration genetic algorithm randomly divides a large population into several small with an identical population number. The migration mechanism among the populations is used to replace the screening mechanism of the selection operator. Operations such as the crossover operator and the mutation operator also are improved. Simulation results show that the multi-population migration genetic algorithm (MPMGA) is not only suitable for simulation maps of various scales and various obstacle distributions, but also has superior performance and effectively solves the problems of the standard genetic algorithm. View Full-Text
Keywords: genetic algorithm; path planning; multi-population; migration mechanism; mobile robot genetic algorithm; path planning; multi-population; migration mechanism; mobile robot
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Hao, K.; Zhao, J.; Yu, K.; Li, C.; Wang, C. Path Planning of Mobile Robots Based on a Multi-Population Migration Genetic Algorithm. Sensors 2020, 20, 5873.

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