Ship Path Planning and Collision Avoidance Based on Improved Ant Colony Algorithm
In recent years,ship is gradually developing in the direction of intelligence and autonomy.Meanwhile,ship path planning,as the basis for implementing ship intelligence,has become the hotspot of research in academia.Ant colony algorithm,as one of the most commonly used meta-heuristic algorithms,has achieved good results in path planning,but it still has some defects.To solve the problems of slow convergence speed and low path safety in implementing ship path planning using ant colony algorithm,heuristic and fusion strategies are adopted to improve the algorithm.By introducing artificial potential field,the efficiency of the algorithm is improved.The constraint functions of path length,path safety and path smoothness are integrated into the pheromone update rules to ensure the safety of the path.Static path planning algorithm based on hybrid ant colony is designed,and the ship collision avoidance process is added to construct the dynamic path planning algorithm.In order to verify the feasibility and effectiveness of the algorithm,various simulation environments are designed for comparative analysis.The results show that the improved ant colony algorithm has faster convergence speed,and the path planning is more practical.
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