全局未知环境下智能群体群集运动与避障控制

研究了在全局环境未知且存在静态障碍物的情况下,智能群体的群集运动控制问题.模型在人工势能结合速度一致策略的基础上,利用了滚动窗口的方法实时产生虚拟领航者引导群体向目标位置运行;并利用极限环方法解决了群体避障问题.基于滚动窗口方法构造的虚拟领航者,充分地利用了实时测得的局部环境信息,具有自适应性;极限环方法避障使得群体能够平滑地绕过障碍物,克服了传统人工势场法避障的局部最小问题.

Flocking with obstacle avoidance of the intelligent swarm in global unknown environment

The flocking with obstacle avoidance in global unknown environment is studied.Based on the strategy of combining artifical potential with velocity consensus,the swarm is navigated to goal by virtual leader which is produced with rolling window method,and the obstacle avoidance is solved by the limit-cycle method.Virtual leader produced by the rolling window method utilizes fully local information,which has self-adaptability,and the limit-cycle method makes the swarm avoid obstacles smoothly,and goes over local minimum in traditional artificial potential field.