| Summary: | 碩士 === 國立臺灣師範大學 === 電機工程研究所 === 102 === Path planning for mobile robots needs to consider several issues including the shortest path, obstacle avoidance, and computation efficiency, which can be regarded as an optimization problem. Taking advantage of the genetic algorithms to solve various optimization problems, this paper first proposes a Cooperative Genetic Optimization (CGO) Algorithm, including the establishment of an elite policy and larger selection region to minimize the occurrence of local optima so as to increase the speed of convergence. Based on the proposed CGO, a global path planning approach for robots is then presented. As a result, the proposed method leads to a better performance to reach the goal in terms of a safer and shorter path in comparison with the traditional genetic algorithm. Considering of App development is very popular recently. In this paper, App based development of robots path planning using Cooperative Genetic Optimization is a great contribution and innovation for development of indoor mobile robot navigation.
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