Obstacle avoidance planning of space manipulator end-effector based on improved ant colony algorithm.

Dongsheng Zhou,Lan Wang,Qiang Zhang

doi:10.1186/s40064-016-2157-x

Dongsheng Zhou, Lan Wang + Show 1 more

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Journal: SpringerPlus	Publication Date: Apr 23, 2016
Citations: 14	License type: CC BY 4.0

Affiliation: Dalian University

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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.

Highlights

A space manipulator system is composed of system body and its on-board manipulator
Space debris and cabin peripheral testing devices have the potential to be obstacles for space manipulator in the process of on-orbit operation, and the collisions occurred between the manipulator and the obstacles will interfere with on-orbit operation to complete the task, and do harm to the manipulator system and operation personnel
Obstacle avoidance planning based on improved ant colony algorithm Inspired by the fact that ants always find a shortest path between the food and the nest during the foraging process, M

Summary

Introduction

A space manipulator system is composed of system body (satellite) and its on-board manipulator. Firstly we establish models for the space manipulator and the environment, and transform the search strategy, transfer rules (Hao and Wang 2010) and pheromone update methods to improve the ant colony algorithm, and the improved ant colony algorithm is used to search the better obstacle avoidance path.

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