A dynamic zone estimation method using cumulative voxels for autonomous driving

• Published in: International journal of advanced robotic systems Vol. 14; no. 1
• Main Authors: Lee, Seongjo, Cho, Seoungjae, Sim, Sungdae, Kwak, Kiho, Park, Yong Woon, Cho, Kyungeun
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 17.01.2017; Sage Publications Ltd; SAGE Publishing
• Subjects: Driving; Ground truth; Lidar; Object motion; Obstacle avoidance; Unmanned vehicles; dynamic object; LIDAR; Dynamic zone; unmanned ground vehicle; cumulative voxels
• ISSN: 1729-8806; 1729-8814
• DOI: 10.1177/1729881416687130

Obstacle avoidance and available road identification technologies have been investigated for autonomous driving of an unmanned vehicle. In order to apply research results to autonomous driving in real environments, it is necessary to consider moving objects. This article proposes a preprocessing method to identify the dynamic zones where moving objects exist around an unmanned vehicle. This method accumulates three-dimensional points from a light detection and ranging sensor mounted on an unmanned vehicle in voxel space. Next, features are identified from the cumulative data at high speed, and zones with significant feature changes are estimated as zones where dynamic objects exist. The approach proposed in this article can identify dynamic zones even for a moving vehicle and processes data quickly using several features based on the geometry, height map and distribution of three-dimensional space data. The experiment for evaluating the performance of proposed approach was conducted using ground truth data on simulation and real environment data set.