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Springerplus

Title:		Obstacle avoidance planning of space manipulator end-effector based on improved ant colony algorithm
Author(s):		Zhou D; Wang L; Zhang Q;
Address:		"Key Laboratory of Advanced Design and Intelligent Computing, Ministry of Education, Dalian University, Dalian, 116622 China"
Journal Title:		Springerplus
Year:		2016
Volume:		20160423
Issue:
Page Number:		509 -
DOI:		10.1186/s40064-016-2157-x
ISSN/ISBN:		2193-1801 (Print) 2193-1801 (Electronic) 2193-1801 (Linking)
Abstract:		"With the development of aerospace engineering, the space on-orbit servicing has been brought more attention to many scholars. Obstacle avoidance planning of space manipulator end-effector also attracts increasing attention. This problem is complex due to the existence of obstacles. Therefore, it is essential to avoid obstacles in order to improve planning of space manipulator end-effector. In this paper, we proposed an improved ant colony algorithm to solve this problem, which is effective and simple. Firstly, the models were established respectively, including the kinematic model of space manipulator and expression of valid path in space environment. Secondly, we described an improved ant colony algorithm in detail, which can avoid trapping into local optimum. The search strategy, transfer rules, and pheromone update methods were all adjusted. Finally, the improved ant colony algorithm was compared with the classic ant colony algorithm through the experiments. The simulation results verify the correctness and effectiveness of the proposed algorithm"
Keywords:		Improved ant colony algorithm Obstacle avoidance Path planning Space manipulator;
Notes:		"PubMed-not-MEDLINEZhou, Dongsheng Wang, Lan Zhang, Qiang eng Switzerland 2016/05/18 Springerplus. 2016 Apr 23; 5:509. doi: 10.1186/s40064-016-2157-x. eCollection 2016"