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Interactive Presentation
DOI: 10.4230/OASIcs.ASD.2019.8
TrueView: A LIDAR Only Perception System for Autonomous Vehicle (Interactive Presentation)

Authors: Mohammed Yazid Lachachi, Mohamed Ouslim, Smail Niar, and Abdelmalik Taleb-Ahmed

Published in: OASIcs, Volume 68, Workshop on Autonomous Systems Design (ASD 2019)

Abstract
Real time perception and understanding of the environment is essential for an autonomous vehicle. To obtain the most accurate perception, existing solutions propose to combine multiple sensors. However, a large number of embedded sensors in the vehicle implies to process a large amount of data thus increasing the system complexity and cost. In this work, we present a novel approach that uses only one LIDAR sensor. Our approach enables reducing the size and complexity of the used machine learning algorithm. A novel approach is proposed to generate multiple 2D representation from 3D points cloud using the LIDAR sensor. The obtained representation solves the sparsity and connectivity issues encountered with LIDAR-based solution.
Cite as

Mohammed Yazid Lachachi, Mohamed Ouslim, Smail Niar, and Abdelmalik Taleb-Ahmed. TrueView: A LIDAR Only Perception System for Autonomous Vehicle (Interactive Presentation). In Workshop on Autonomous Systems Design (ASD 2019). Open Access Series in Informatics (OASIcs), Volume 68, pp. 8:1-8:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{lachachi_et_al:OASIcs.ASD.2019.8,
  author =	{Lachachi, Mohammed Yazid and Ouslim, Mohamed and Niar, Smail and Taleb-Ahmed, Abdelmalik},
  title =	{{TrueView: A LIDAR Only Perception System for Autonomous Vehicle}},
  booktitle =	{Workshop on Autonomous Systems Design (ASD 2019)},
  pages =	{8:1--8:10},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-102-3},
  ISSN =	{2190-6807},
  year =	{2019},
  volume =	{68},
  editor =	{Saidi, Selma and Ernst, Rolf and Ziegenbein, Dirk},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.ASD.2019.8},
  URN =		{urn:nbn:de:0030-drops-103411},
  doi =		{10.4230/OASIcs.ASD.2019.8},
  annote =	{Keywords: Ranging Data, Computer Vision, Machine Learning}
}
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