A novel path planning algorithm based on plant growth mechanism

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• 作者：Yaoming Zhou ; Yongchao Wang ; Xuzhi Chen ; Lei Zhang ; Kan Wu
• 关键词：Path planning ; Plant growth ; Bud ; Light intensity ; Branch
• 刊名：Soft Computing
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：21
• 期：2
• 页码：435-445
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Computational Intelligence; Artificial Intelligence (incl. Robotics); Mathematical Logic and Foundations; Control, Robotics, Mechatronics;
• 出版者：Springer Berlin Heidelberg
• ISSN：1433-7479
• 卷排序：21

文摘

We propose a bio-inspired computing algorithm based on plant growth mechanism and describe its application in path planning in this paper. The basic rules of the algorithm include phototropism, negative geotropism, apical dominance, and branch in plant growth. The starting point of the algorithm is the seed germ (first bud) and the target point of the algorithm is the light source. The discretization of the plant growth process is used to realize computation in computer. The plant growth behavior in each iteration is assumed to be the same. The algorithm includes six steps: initialization, light intensity calculation, random branch, growth vector calculation, plant growth and path output. Several two-dimensional path planning problems are used to validate the algorithm. The test results show that the algorithm has good path planning ability and provides a novel path planning approach.