loading
Papers

Research.Publish.Connect.

Paper

Authors: Burtin Gabriel 1 ; Bonnin Patrick 2 and Malartre Florent 1

Affiliations: 1 4D-Virtualiz, 10 Allee Evariste Galois, Clermont-Ferrand and France ; 2 LISV, Universite de Versailles St Quentin, 10-12 Avenue de l’Europe Velizy and France

ISBN: 978-989-758-380-3

Keyword(s): Line Segment Detection, Algorithm Optimization, Camera-lidar Sensor Fusion, Localization, Extended Kalman Filter.

Related Ontology Subjects/Areas/Topics: Informatics in Control, Automation and Robotics ; Mobile Robots and Autonomous Systems ; Robot Design, Development and Control ; Robotics and Automation ; Sensors Fusion ; Signal Processing, Sensors, Systems Modeling and Control ; Virtual Environment, Virtual and Augmented Reality

Abstract: The objective of this work is to use efficiently various sensors to create a SLAM system. This algorithm has to be fast (real-time), computationally light and efficient enough to allow the robot to navigate in the environment. Because other processes embedded require large amount of cpu-time, our objective was to use efficiently complementary sensors to obtain a fairly accurate localization with minimal computation. To reach this, we used a combination of two sensors: a 2D lidar and a camera, mounted above each other on the robot and oriented toward the same direction. The objective is to pinpoint and cross features in the camera and lidar FOV. Our optimized algorithms are based on segments detection. We decided to observe intersections between vertical lines seen with the camera and locate them in 3D with the ranges provided by the 2D lidar. First we implemented a RGB vertical line detector using RGB gradient and linking process, then a lidar data segmentation with accelerated comput ation and finally we used this feature detector in a Kalman filter. The final code is evaluated and validated using an advanced real-time robotic simulator and later confirmed with a real experiment. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 34.229.131.116

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Gabriel, B.; Patrick, B. and Florent, M. (2019). Camera and Lidar Cooperation for 3D Feature Extraction.In Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-758-380-3, pages 23-33. DOI: 10.5220/0007808900230033

@conference{icinco19,
author={Burtin Gabriel. and Bonnin Patrick. and Malartre Florent.},
title={Camera and Lidar Cooperation for 3D Feature Extraction},
booktitle={Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2019},
pages={23-33},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007808900230033},
isbn={978-989-758-380-3},
}

TY - CONF

JO - Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - Camera and Lidar Cooperation for 3D Feature Extraction
SN - 978-989-758-380-3
AU - Gabriel, B.
AU - Patrick, B.
AU - Florent, M.
PY - 2019
SP - 23
EP - 33
DO - 10.5220/0007808900230033

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.