License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.ASD.2019.8
URN: urn:nbn:de:0030-drops-103411
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Lachachi, Mohammed Yazid ; Ouslim, Mohamed ; Niar, Smail ; Taleb-Ahmed, Abdelmalik

TrueView: A LIDAR Only Perception System for Autonomous Vehicle (Interactive Presentation)

OASIcs-ASD-2019-8.pdf (3 MB)


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.

BibTeX - Entry

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

Keywords: Ranging Data, Computer Vision, Machine Learning
Collection: Workshop on Autonomous Systems Design (ASD 2019)
Issue Date: 2019
Date of publication: 28.03.2019

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