Autonomous Racing: An Exploration of Localization, Waypoint Following, and Actuation for High-Speed Autonomous Vehicles
Description
The objective of this project was to research and experimentally test methods of localization, waypoint following, and actuation for high-speed driving by an autonomous vehicle. This thesis describes the implementation of LiDAR localization techniques, Model Predictive Control waypoint following, and communication for actuation on a 2016 Chevrolet Camaro, Arizona State University’s former EcoCAR. The LiDAR localization techniques include the NDT Mapping and Matching algorithms from the open-source autonomous vehicle platform, Autoware. The mapping algorithm was supplemented by that of Google Cartographer due to the limitations of map size in Autoware’s algorithms. The Model Predictive Control for waypoint following and the computer-microcontroller-actuator communication line are described. In addition to this experimental work, the thesis discusses an investigation of alternative approaches for each problem.
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2020-05
Agent
- Author (aut): Copenhaver, Bryce Stone
- Thesis director: Berman, Spring
- Committee member: Yong, Sze Zheng
- Contributor (ctb): Dean, W.P. Carey School of Business
- Contributor (ctb): Engineering Programs
- Contributor (ctb): Barrett, The Honors College