基于改进RRT*算法的井下巷道漫游路径规划方法OA北大核心CSTPCD

In allusion to the problem of collision detection and path planning in the mine lane virtual reality process of 3D visualization mine lane,such as the action trajectory reproduction of underground coal mine lane operators and coal mine lane roaming,an improved method is proposed to solve the problem of seeking the optimal path in the complex environment and high-dimensional space of underground coal mine lane by combining the improved rapidly-exploring random tree star(RRT*)algorithm with the greedy algorithm.In the improved method,the first exploration strategy and greedy strategy are used to solve the problem that RRT algorithm is difficult to solve the optimal feasible path and the problem of RRT* algorithm motion path oscillation.The Matlab simulation experiment platform verifies that the proposed planning method can obtain satisfactory obstacle avoidance planning path,and in comparison with RRT* algorithm,this method can reduce most useless path search and memory storage of path edge path,improve the efficiency of path planning,effectively solve the problem of motion path oscillation in the process of virtual reality,and realize smooth path planning.