Aiming at seeking optimal motion paths for Free-flying Space Robot (FFSR) in the obstacle environment, Ant Colony Algorithm (ACA) for obstacle avoidance motion planning has been proposed. Firstly, FFSR kinematics and motion path model has been established on the basis of linear momentum and angular momentum conservation laws followed by FFSR in a space microgravity environment. Secondly, ACA for FFSR collision has been proposed and a key research has been made on how to determine objective function, how to select path configurations and how to update pheromones and algorithm and realize the critical steps. Finally, the correctness and effectiveness of the algorithm proposed has been verified via computer simulation. The research results indicate that ACA based on swarm intelligence provides a new motion planning strategy and idea for FFSR collision avoidance motion planning and has good application prospect.
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