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Sensors (Basel)

Title:		3D Path Planning for the Ground Robot with Improved Ant Colony Optimization
Author(s):		Wang L; Kan J; Guo J; Wang C;
Address:		"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China. wanglanfei@bupt.edu.cn. School of Technology, Beijing Forestry University, Beijing 100083, China. kanjm@bjfu.edu.cn. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China. guojun@bupt.edu.cn. School of Technology, Beijing Forestry University, Beijing 100083, China. bjfu_wangchao@163.com"
Journal Title:		Sensors (Basel)
Year:		2019
Volume:		20190216
Issue:		4
Page Number:		-
DOI:		10.3390/s19040815
ISSN/ISBN:		1424-8220 (Electronic) 1424-8220 (Linking)
Abstract:		"Path planning is a fundamental issue in the aspect of robot navigation. As robots work in 3D environments, it is meaningful to study 3D path planning. To solve general problems of easily falling into local optimum and long search times in 3D path planning based on the ant colony algorithm, we proposed an improved the pheromone update and a heuristic function by introducing a safety value. We also designed two methods to calculate safety values. Concerning the path search, we designed a search mode combining the plane and visual fields and limited the search range of the robot. With regard to the deadlock problem, we adopted a 3D deadlock-free mechanism to enable ants to get out of the predicaments. With respect to simulations, we used a number of 3D terrains to carry out simulations and set different starting and end points in each terrain under the same external settings. According to the results of the improved ant colony algorithm and the basic ant colony algorithm, paths planned by the improved ant colony algorithm can effectively avoid obstacles, and their trajectories are smoother than that of the basic ant colony algorithm. The shortest path length is reduced by 8.164%, on average, compared with the results of the basic ant colony algorithm. We also compared the results of two methods for calculating safety values under the same terrain and external settings. Results show that by calculating the safety value in the environmental modeling stage in advance, and invoking the safety value directly in the path planning stage, the average running time is reduced by 91.56%, compared with calculating the safety value while path planning"
Keywords:		3D space ant colony optimization ground robot path planning;
Notes:		"PubMed-not-MEDLINEWang, Lanfei Kan, Jiangming Guo, Jun Wang, Chao eng 61273217/Jun Guo/ 31570713/Jiangming Kan/ Switzerland 2019/02/20 Sensors (Basel). 2019 Feb 16; 19(4):815. doi: 10.3390/s19040815"