A New Challenge: Path Planning for Autonomous Truck of Open-Pit Mines in The Last Transport Section

Abstract

During the operation of open-pit mining, the loading position of a haulage truck often changes, bringing a new challenge concerning how to plan an optimal truck transportation path considering the terrain factors. This paper proposes a path planning method based on a high-precision digital map. It contains two parts: (1) constructing a high-precision digital map of the cutting zone and (2) planning the optimal path based on the modified Hybrid A* algorithm. Firstly, we process the high-precision map based on different terrain feature factors to generate the obstacle cost map and surface roughness cost map of the cutting zone. Then, we fuse the two cost maps to generate the final cost map for path planning. Finally, we incorporate the contact cost between tire and ground to improve the node extension and path smoothing part of the Hybrid A* algorithm and further enhance the algorithm’s capability of avoiding the roughness. We use real elevation data with different terrain resolutions to perform random tests and the results show that, compared with the path without considering the terrain factors, the total transportation cost of the optimal path is reduced by 10%–20%. Moreover, the methods demonstrate robustness.

Open-Pit Map: An HD Map Data Model for Open-Pit Mines

“…Different elements in the HD map for open-pit mines were provided in previous literatures [8][9][10]. But the application scenarios of open-pit mines were not closely connected with the elements.…”

“…Kasper Johansen [8] used unmanned aerial vehicles to automatically map indicators of safety, stability, and sustainability of rehabilitation efforts in coalmine sites. Ziyu Zhao and Lin Bi [9] proposed a path planning method based on a high-precision digital map. Xiaowei Wang et al [10] proposed an HD map construction and update system for autonomous driving in open-pit mines.…”

Virtual Surfaces and Attitude Aware Planning and Behaviours for Negative Obstacle Navigation

“…Minor changes to GridMap were made in order to load parameters differently and make minor optimisations. The filter used to identify fatal obstacles was similar to the one used in [30] with an added step to remove small concavities that the vehicle can easily traverse and to use vertical sections in three directions instead of four.…”