Fast Method for Long-Distance Off-Road Path Planning based on Terrain Data

The fast path planning of motor vehicles in the off-road environment is of great significance in the fields of field search and rescue, emergency rescue, and military operations. In the above scenarios, with the increase of spatial dimension, the computational complexity of traditional path search algorithms increases exponentially, and may not be able to be calculated within a given time. To solve the above deficiencies, this paper proposes a heuristic algorithm with directional pointing as a search strategy, combining the characteristics of off-road path planning that is not restricted by road network traffic and the shortest straight line between two points. In order to further improve the solution quality, a Dijkstra segmentation algorithm with directional pointing is proposed. This algorithm finds the optimal path through Dijkstra algorithm in a low-precision environment model and divides the path into segments. Each segment is oriented in a direction. Route search is performed as a search strategy to quickly plan passage schemes in long-distance off-road route planning. In order to verify the effectiveness of the algorithm, this paper uses the digital elevation model data of a city in Shanxi Province to conduct experiments and introduces the window movement method to perform preliminary slope calculation and trafficability analysis of the terrain, build an off-road environment model, and call the path search algorithm to carry out path planning. The experimental results show that the computational efficiency of the algorithm proposed in this paper has been greatly improved compared to the Dijkstra algorithm, and the length of the planned path is close to the optimal solution. © 2022, Science Press. All right reserved.