Obstacle detection and tracking in an urban environment Using 3D LiDAR and a Mobileye 560

In order to navigate in an urban environment, a vehicle must be able to reliably detect and track dynamic obstacles such as vehicles, pedestrians, bicycles, and motorcycles. This paper presents a sensor fusion algorithm which combines tracking information from a Mobileye 560 and a Velodyne HDL-64E. The Velodyne tracking module first extracts obstacles by removing the ground plane points and then segmenting the remaining points using Euclidean Cluster Extraction. The Velodyne tracking module then uses the Kuhn-Munkres algorithm to associate Velodyne obstacles of the same type between time steps. The sensor fusion module associates and tracks obstacles from both the Velodyne and Mobileye tracking modules. It is able to reliably associate the same Velodyne and Mobileye obstacle between frames, although the Velodyne tracking module only provides robust tracking in simple scenes such as bridges.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2017

Author dc:creator

• Lane, Veronica M

Advisor dc:contributor.advisor

• Sertac Karaman.

• Electrical Engineering and Computer Science.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/113295

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/113295