Abstract:

To meet the needs for the guidance of algorithm search in a complex environment, the optimality of global path in a static environment, and the security of real-time obstacle avoidance in a dynamic environment for path planning of cultural and tourism service robots, an algorithm based on the fusion of the improved A* algorithm and the dynamic window approach was proposed. Firstly, based on the traditional A* algorithm, a more accurate search neighborhood selection strategy was adopted, the obstacle occupation grid rate was introduced to quantify map information, and the heuristic function and weight coefficients were dynamically adjusted. Secondly, the concept of safe distance was introduced, and a cubic polyline optimization method was proposed to eliminate redundant nodes and inflection points, enhancing the smoothness of the path. For the narrow channel environment, an adaptive arc optimization method was proposed to make the path more consistent with the kinematic constraints of the robot. The integration of the vertical distance cost function of dynamic obstacles effectively reduced the risk of conflicts and collisions between the robot and dynamic obstacles. Finally, the improved A* algorithm was integrated with the dynamic window method, selecting the key path point as the temporary target point for the dynamic window method, and applying the dynamic window method segmentally for local real-time path correction. Experimental results demonstrated that this fusion algorithm has search guidance, global path optimality and dynamic obstacle avoidance capabilities, and can reach the target point safely and quickly, thus offering certain application value.

Key words: cultural tourism service robot, environment modeling, path planning, real-time obstacle avoidance, A* algorithm, dynamic window approach