A Generalized 3-D Path Planning Method for Robots Using Genetic Algorithm with An Adaptive Evolution Process
Refereed conference paper presented and published in conference proceedings


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摘要Traditionally, path planning for robots is modeled as optimization problems. One of the most commonly used optimization strategies is Genetic Algorithm (GA) since it always guarantees a nearly shortest path even a global path can not be obtained within a reasonable time. In fact, the performance enhancement of GA is still an open topic for researchers by designing different genetic operators. In addition to this, we propose a new criterion for the selection of genetic operators during evolution in order to further facilitate the searching efficiency. In this paper, we propose a generalized 3-D path planning method for robots using GA with an adaptive evolution process. Based on the framework of traditional GA, we first introduce a new genetic operator, called Bind-NN which randomly divides and recombines an elitist chromosome based on nearest neighbor. We also show that by choosing the fitness variance of the shortest path in last generations as a guidance in selecting genetic operators during evolution, the search efficiency can be significantly improved, thus proposing a genetic operators selection scheme. In the latter part of this paper, we present the algorithm evaluation by stimulating a sample path planning problem on a structural frame. With the use of the proposed genetic operator and selection scheme, experimental results show a significant improvement in terms of search effectiveness and efficiency.
著者Chung WK, Xu YS
會議名稱8th World Congress on Intelligent Control and Automation (WCICA)
會議開始日06.07.2010
會議完結日09.07.2010
會議地點Jinan
會議國家/地區中國
出版年份2010
月份1
日期1
出版社IEEE
頁次1354 - 1360
電子國際標準書號978-1-4244-6712-9
語言英式英語
關鍵詞3-D path planning; adaptive evolution; genetic algorithm
Web of Science 學科類別Automation & Control Systems; Engineering; Engineering, Electrical & Electronic

上次更新時間 2021-19-01 於 00:19