Improving Object Detection Through Multi-Perspective LiDAR Fusion

Karl Schrab, Felix Hilgerdenaar, Robert Protzmann, Ilja Radusch

2025

Abstract

Detection of relevant objects in the driving environment is crucial for autonomous driving. Using LiDAR scans and image detection based on neural networks for this task is one possibility and already well researched. With advances in the V2N communication stack, the task of object detection can be shifted towards the edge-cloud, which would enable collaborative data collection and consideration of multiple perspectives in preparation for the detection. In this paper, we present an initial analysis of this idea, by utilizing the Eclipse MOSAIC co-simulation framework to develop and test the fusion of multi-perspective LiDAR frames and subsequent object detection. We generate synthetic LiDAR data from the views of multiple vehicles for detection training and use them to assess the robustness of our approach in regard to positioning and latency requirements. We found that a data fusion from multiple perspectives primarily improves detection of largely or fully occluded objects, which could help situation recognition and, therefore, decision making.

Paper Citation

in Harvard Style

Schrab K., Hilgerdenaar F., Protzmann R. and Radusch I. (2025). Improving Object Detection Through Multi-Perspective LiDAR Fusion. In Proceedings of the 11th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS; ISBN 978-989-758-745-0, SciTePress, pages 448-457. DOI: 10.5220/0013283600003941

in Bibtex Style

@conference{vehits25,
author={Karl Schrab and Felix Hilgerdenaar and Robert Protzmann and Ilja Radusch},
title={Improving Object Detection Through Multi-Perspective LiDAR Fusion},
booktitle={Proceedings of the 11th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS},
year={2025},
pages={448-457},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013283600003941},
isbn={978-989-758-745-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS
TI - Improving Object Detection Through Multi-Perspective LiDAR Fusion
SN - 978-989-758-745-0
AU - Schrab K.
AU - Hilgerdenaar F.
AU - Protzmann R.
AU - Radusch I.
PY - 2025
SP - 448
EP - 457
DO - 10.5220/0013283600003941
PB - SciTePress