动态环境下基于多人工鱼群算法和避碰规则库的机器人路径规划

摘要

为了提高机器人路径规划的速度、环境适应能力和高效动态避碰问题,提出了一种基于多人工鱼群的机器人路径规划算法和基于避碰规则库的动态避障算法.该算法中,人工鱼以其与目标点的距离为食物浓度,两个邻近栅格的距离为步长,其觅食行作为默认行为,在一定条件下执行聚群或追尾动作,并采用两鱼群双向搜索机制在静态环境下规划出较优路径.在此基础上,机器人查询动态避障规则库获得避碰方法,从而实现与动态障碍的避碰.大量仿真实验结果表明,该方法具有较高的收敛速度和较强的搜索能力,能在非常复杂的动静态障碍环境中,迅速规划出一条安全避碰的优化路径.%In order to improve the convergence speed and the environmental adaptability of the path planning algorithm, a robot path planning algorithm based on multi-artificial fish-swarm is proposed. We present also a dynamic obstacle avoidance algorithm based on the rule-base of collision avoidance in dynamic environment to avoid collisions with the moving obstacles. In our approach, the distance between a fish and a goal is defined as food concentration and the distance between two neighbor grids is defined as step length. The preying behavior of fishes is regard as default behavior and perform clusters act or rear-end act is activated in some certain condition. Then the optimal path in static environment is planned by the search mechanism of bi-directional fish-swarms. After that, the effective collision avoidance behavior is obtained, from the obtained dynamic obstacle information through sensors.Many simulation experiments have shown that the algorithm has a fast convergence speed and strong search capability.Even in complex environments which have static and dynamic obstacles,it can avoid collision safely and plan an optimal path rapidly at the same time.