复杂动态环境下基于改进的CautiousBug算法的机器人路径规划

Path Planning of Robots Based on the Improved CautiousBug Algorithm in Complex and Dynamic Environment

通过对CautiousBug算法进行改进,提出了一种复杂动态环境下移动机器人局部路径规划方法.首先,针对移动机器人局部路径规划中局部极值点问题,CautiousBug算法中机器人在沿障碍物边缘绕行时,基于螺线绕行规则不断地调整绕行方向以逃离局部极值点,但调整模式单一,缺乏灵活性,为了使机器人更易快速的逃离局部极值点,本文将目标点作为参考信息,在螺线绕行规则中添加了绕行方向调整条件.其次,为了使机器人能安全避开随机移动的障碍物,在CautiousBug算法中添加了动态障碍物避碰规则,该避碰规则考虑了路径的局部优化,最终可以使机器人绕过随机移动的障碍物并规划出一条较优的安全路径.仿真结果验证了改进算法在复杂动态环境下的实时性和有效性.

For a single mobile robot in a complex and dynamic environment, a local path planning method is presen- ted based on the improved CautiousBug algorithm. The original CautiousBug algorithm uses the spiral searching strategy to address the problem of local minimum point, where the motion direction of the robot along an obsta- cle boundary is frequently adjusted to flee the local minimum point; however, the pattern of adjustment is very simple and lacks flexibility. In the improved one, to make the robot flee the local minimum point more quickly and easily, we add a condition for adjusting the following direction to the spiral searching strategy, where the target point is regarded as a reference point. Secondly, a rule to safely avoid the obstacles with random motion is also constructed in the improved one, where local optimization of the path is considered. The rule can make the robot bypass dynamic obstacles and find a better and safety path. Simulation results demonstrate the effec- tiveness and real time property of the improved method in complex and dynamic environments.