移动机器人全覆盖路径规划算法研究

针对静态未知环境下移动机器人全覆盖路径规划问题,提出了一种改进优先级蚁群算法。该算法首先通过机器人本体上的传感器构建基于动态栅格法的工作环境;综合考虑栅格属性、机器人转向、邻域栅格距离和未覆盖区域面积大小的基础上构造优先级启发规则,然后利用该规则进行路径全覆盖工作。针对机器人工作过程中出现的死锁问题,文章提出采用蚁群算法寻找逃离死区的最优路径,从而保证机器人实现路径全覆盖,并使覆盖路径的重复率尽可能小。仿真实验中,通过与传统算法比较,验证所提算法能在保证面积覆盖率为100%的同时,降低了死锁次数和轨迹重复率,从而提高了机器人工作效率。

Research on the Complete-Coverage Path Planning Algorithm of Mobile Robot

Aiming at the problem of complete-coverage path planning of mobile robot under static and unknown environment,an improved heuristic rule with ant colony algorithm is proposed.The algorithm firstly constructs a working environment based on the dynamic grid method through sensors on the robot body.A new priority heuristic rule that covers the entire path is constructed,considering the attributes of the grid,the robot steering,the distance between the neighboring grids,and the size of the uncovered area.In order to solve the problem of deadlock,this paper proposes an ant colony algorithm to find the optimal path and escape from the dead zone,so as to ensure the robot achieving complete-coverage and making the coverage path repetition rate as small as possible.Compared with the existing algorithms,simulation results are used to verify that the proposed algorithm has reduced the numbers of deadlock and trajectory repetition rate while ensuring the area coverage rate is 100%,and the work efficiency of robot is improved.