Fast Local Planning and Mapping in Unknown Off-Road Terrain
This work addresses the challenge of autonomous navigation in unstructured off-road settings, which is incremental as it builds on existing planning and mapping techniques.
The paper tackles the problem of real-time navigation in unknown off-road terrain by developing a fast on-line mapping and planning solution that operates at 30 Hz, enabling high-speed traversal in various environments.
In this paper, we present a fast, on-line mapping and planning solution for operation in unknown, off-road, environments. We combine obstacle detection along with a terrain gradient map to make simple and adaptable cost map. This map can be created and updated at 10 Hz. An A* planner finds optimal paths over the map. Finally, we take multiple samples over the control input space and do a kinematic forward simulation to generated feasible trajectories. Then the most optimal trajectory, as determined by the cost map and proximity to A* path, is chosen and sent to the controller. Our method allows real time operation at rates of 30 Hz. We demonstrate the efficiency of our method in various off-road terrain at high speed.