This paper presents a novel approach for local 3D environment representation for autonomous unmanned ground vehicle (UGV) navigation called On Visible Point Clouds Mesh(OVPC Mesh). Our approach represents the surrounding of the robot as a watertight 3D mesh generated from local point cloud data in order to represent the free space surrounding the robot. It is a conservative estimation of the free space and provides a desirable trade-off between representation precision and computational efficiency, without having to discretize the environment into a fixed grid size. Our experiments analyze the usability of the approach for UGV navigation in rough terrain, both in simulation and in a fully integrated real-world system. Additionally, we compare our approach to well-known state-of-the-art solutions, such as Octomap and Elevation Mapping and show that OVPC Mesh can provide reliable 3D information for trajectory planning while fulfilling real-time constraints.
@article{arxiv.1811.10266,
title = {OVPC Mesh: 3D Free-space Representation for Local Ground Vehicle Navigation},
author = {Fabio Ruetz and Emili Hernández and Mark Pfeiffer and Helen Oleynikova and Mark Cox and Thomas Lowe and Paulo Borges},
journal= {arXiv preprint arXiv:1811.10266},
year = {2018}
}
Comments
7 pages, ICRA 2019 submission, video https://www.youtube.com/watch?v=8b0w56bg0WM&t=81s