S-RRT path planning based on slime mould biological model  

作　　者：You Yue Li Qinghua Chen Xiyuan Zhang Zhao Mu Yaqi Feng Chao 

机构地区：[1]School of Electrical Engineering and Automation,Qilu University of Technology(Shandong Academy of Sciences),Jinan 250353,China [2]Jinan Engineering Laboratory of Human-machine Intelligent Cooperation,Qilu University of Technology(Shandong Academy of Sciences),Jinan 250353,China [3]School of Electronic and Information Engineering(Department of Physics),Qilu University of Technology(Shandong Academy of Sciences),Jinan 250353,China [4]School of Instrument Science and Engineering,Southeast University,Nanjing 210018,China [5]Institute of Automation,Qilu University of Technology(Shandong Academy of Sciences),Jinan 250101,China

出　　处：《The Journal of China Universities of Posts and Telecommunications》2021年第6期55-64,共10页中国邮电高校学报（英文版）

基　　金：supported by the National Natural Science Foundation of China (61701270)。

摘　　要：To improve the security and effectiveness of mobile robot path planning, a slime mould rapid-expansion random tree(S-RRT) algorithm is proposed. This path planning algorithm is designed based on a biological optimization model and a rapid-expansion random tree(RRT) algorithm. S-RRT algorithm can use the function of optimal direction to constrain the generation of a new node. By controlling the generation direction of the new node, an optimized path can be achieved. Thus, the path oscillation is reduced and the planning time is shortened. It is proved that S-RRT algorithm overcomes the limitation of paths zigzag of RRT algorithm through theoretical analysis. Experiments show that S-RRT algorithm is superior to RRT algorithm in terms of safety and efficiency.

关 键 词：mobile robot path planning rapid-expansion random tree(RRT) slime mould 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]