Obstacle detection and tracking in an urban environment Using 3D LiDAR and a Mobileye 560
Name
1017988848-MIT.pdf
Description
Full printable version
Size
4.5 MB
Format
Adobe PDF
Checksum (MD5)
d35ebf4730e9bcffcc65ea2f4f5e6bd4
Author(s)
Lane, Veronica M
Advisor(s)
Sertac Karaman.
Date Issued
2017
Publisher
Massachusetts Institute of Technology
Abstract
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.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 40-41).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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.
Persistent DSpace Link
