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

For a single mobile robot in a complex and dynamic environment,a local path planning method is presented 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 obstacle 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 effectiveness and real time property of the improved method in complex and dynamic environments.