Localizing, modeling, and drifting an autonomous RACECAR

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.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 103-105).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.by Corey H. Walsh.M. Eng