Estimation of Looming from LiDAR

Juan Yepes, Daniel Raviv

2022

Abstract

Looming, traditionally defined as the relative expansion of objects in the observer’s retina, is a fundamental visual cue for perception of threat and can be used to accomplish collision free navigation. The measurement of the looming cue is not only limited to vision and can also be obtained from range sensors like LiDAR (Light Detection and Ranging). In this article we present two methods that process raw LiDAR data to estimate the looming cue. Using looming values, we show how to obtain threat zones for collision avoidance tasks. The methods are general enough to be suitable for any six-degree-of-freedom motion and can be implemented in real-time without the need for fine matching, point-cloud registration, object classification or object segmentation. Quantitative results using the KITTI dataset shows advantages and limitations of the methods.

Paper Citation

in Harvard Style

Yepes J. and Raviv D. (2022). Estimation of Looming from LiDAR. In Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-573-9, pages 455-462. DOI: 10.5220/0011115300003191

in Bibtex Style

@conference{vehits22,
author={Juan Yepes and Daniel Raviv},
title={Estimation of Looming from LiDAR},
booktitle={Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2022},
pages={455-462},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011115300003191},
isbn={978-989-758-573-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Estimation of Looming from LiDAR
SN - 978-989-758-573-9
AU - Yepes J.
AU - Raviv D.
PY - 2022
SP - 455
EP - 462
DO - 10.5220/0011115300003191