# Fast Local Planning and Mapping in Unknown Off-Road Terrain

arXiv: https://arxiv.org/abs/1910.08521 · HTML: https://mlsanity.com/paper/1910.08521/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Oct 2019.

## Built on by (most cited first, 2 of 2)

- [Risk-Aware Off-Road Navigation via a Learned Speed Distribution Map](https://mlsanity.com/paper/2203.13429/) (2022)
- [Motion planning for off-road autonomous driving based on human-like cognition and weight adaptation](https://mlsanity.com/paper/2404.17820/) (2024)

## Abstract (arXiv)

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.