人工鱼群优化算法的移动机器人路径规划研究

Improved Artificial Fish Swarm Optimization Algorithm for Path Planning of Mobile Robot

针对传统人工鱼群算法在移动机器人全局路径规划中存在搜索效率比较低且路径冗余点比较多的问题,提出了基于双向搜索策略的人工鱼群算法。该算法通过正反两个方向交替检索路径的方式来进行全局路径规划,提高了算法在路径规划时的效率以及收敛速度。另外对于规划出的路径冗余节点以及不必要拐点较多的问题,通过对规划好的路径集引入路径平滑处理策略进行路径优化。仿真结果表明,改进后的人工鱼群算法与传统人工鱼群算法相比在收敛速度以及路径搜寻效率上均有较大的提高。最终将改进算法应用到实际的移动机器人中,实验结果证明,改进的算法可以有效解决移动机器人的路径规划问题。

Aiming at the problems of low search efficiency and many redundant points in the global path planning of mobile robots with traditional artificial fish swarm algorithm,an artificial fish swarm algorithm based on bidirectional search strategy was proposed.The algorithm performs global path planning by alternately retrieving paths in both positive and negative directions,which improves the efficiency and convergence speed of the algorithm in path planning.In addition,for the problem of redundant nodes and unnecessary inflection points in the planned path,the path smoothing strategy is introduced to optimize the planned path set.The simulation results show that the improved artificial fish swarm algorithm is better than the traditional artificial fish swarm algorithm in convergence speed and path search efficiency.Finally,the improved algorithm is applied to the actual mobile robot,and the experimental results show that the improved algorithm can effectively solve the global path planning problem of mobile robot.