Elevation Mapping for Locomotion and Navigation using GPU
Takahiro Miki, Lorenz Wellhausen, Ruben Grandia, Fabian Jenelten, Timon Homberger, Marco Hutter
Abstract
Perceiving the surrounding environment is crucial for autonomous mobile robots. An elevation map provides a memory-efficient and simple yet powerful geometric represen-tation of the terrain for ground robots. The robots can use this information for navigation in an unknown environment or perceptive locomotion control over rough terrain. Depending on the application, various post processing steps may be incorpo-rated, such as smoothing, inpainting or plane segmentation. In this work, we present an elevation mapping pipeline leveraging GPU for fast and efficient processing with additional features both for navigation and locomotion. We demonstrated our map-ping framework through extensive hardware experiments. Our mapping software was successfully deployed for underground exploration during DARPA Subterranean Challenge and for various experiments of quadrupedal locomotion.
BibTeX
@inproceedings{iros2022_elevationmapping,
title = {Elevation Mapping for Locomotion and Navigation using GPU},
author = {Takahiro Miki and Lorenz Wellhausen and Ruben Grandia and Fabian Jenelten and Timon Homberger and Marco Hutter},
booktitle = {IROS 2022},
year = {2022}
}