Home // ALLSENSORS 2020, The Fifth International Conference on Advances in Sensors, Actuators, Metering and Sensing // View article

Detection and Classification of Obstacles Using a 2D LiDAR Sensor

Authors:
Alejandro Olivas González
Fernando Torres Medina

Keywords: Mobile robots; LiDAR; 3D map; Low-cost

Abstract:
Detecting and mapping obstacles is an important component in mobile robots. In this paper, we use only an economic 2D Light Detection and Ranging (LiDAR) sensor to make a 3D map of the scene, classifying the scanned data into ground, obstacles and potholes. To do this, the points from the LiDAR are clustered in segments, and then they are classified depending of their height. The method successfully classifies in low dynamic structured environments, and generates compact 3D map that represents the scene with a few points.

Pages: 63 to 66

Copyright: Copyright (c) IARIA, 2020

Publication date: March 22, 2020

Published in: conference

ISSN: 2519-836X

ISBN: 978-1-61208-766-5

Location: Valencia, Spain

Dates: from November 21, 2020 to November 21, 2020