Localizing, modeling, and drifting an autonomous RACECAR

In this thesis, I discuss several topics which are core to the development of car-like autonomous systems, using the small scale autonomous RACECAR platform as a testbed. The ultimate goal of this work was to create an autonomously drifting car, which has been achieved with nonlinear trajectory optimization, and time-varying LQR trajectory tracking. Topics include a discussion of the RACECAR platform, dynamics modeling of car-like systems, robot localization, autonomous RACECAR control, and the design of a custom RACECAR simulator. In developing a high performance particle filter localization algorithm, I designed and implemented a novel algorithm for high performance two-dimensional ray casting in occupancy grid maps, called the Compressed Directional Distance Transform (CDDT). Here, I will discuss the theory and characteristics of the CDDT algorithm, which has been implemented in RangeLibc, my open-source software library.

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

2018

Author dc:creator

• Walsh, Corey H

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/1721.1/119700

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/119700