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In this study, a global path planning method is proposed for the motion of the chassis of a forest harvester to satisfy the requirements of obstacle avoidance when the harvester is working in the forest. First, a distributed plane map is generated in accordance with the characteristics of forest environment. Subsequently, a Ms_BiRRT algorithm is proposed based on the principle of the random search tree algorithm for multi-stage target-guided global path planning, and the path is further optimized. The effectiveness of the Ms_BiRRT algorithm proposed in this study is examined through experimental simulation. Three types of map environments are designed based on the characteristics of the forest environment. The average planning time of the proposed algorithm is extended by 90.69% and 47.37%, the path length is shortened by 10.40% and 8.23%, the total number of nodes is reduced by 81.52% and 54.65%, and the node utilization rate increases from 18.47% and 44.12% to 85.46%, respectively, compared with classical RRT algorithm and two-way RRT algorithm. The path planning algorithm proposed in this study is capable of quickly reaching the target point in different environments, improving the convergence speed of the algorithm, and increasing the efficiency and stability of the forest harvester in the working process based on the initial path guidance and target guidance methods.

Study of a chassis path planning algorithm for a forest harvester