Research on Hybrid Path Planning Algorithm Based on Improved Pigeon Flock and Morphin Algorithm
Aiming at the weak path planning ability of unmanned vehicles in complex environments such as static and dynamic obstacles at the same time,a hybrid path planning algorithm based on pigeon flock algorithm and Morphine algorithm with adaptive weight coefficients is proposed.The first step is to determine the starting point and the end point in the grid map while es-tablishing an environment model.The second step is to add adaptive weight coefficients to the pigeon calculation to make improve-ments to plan a global optimal path.The unmanned vehicle drives according to the global path.When the sensor of the unmanned vehicle detects an unknown static or dynamic obstacle,it immediately calls the Morphine algorithm for local path planning to avoid the obstacle.The unmanned vehicle returns to the original path after avoiding the obstacle and continues to drive to the tar-get point.The effectiveness and feasibility of the hybrid path planning algorithm are verified by simulation experiments and practi-cal applications on unmanned vehicles.
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