Thesis
2-D SCAN-MATCHING APPROACH TO LIDAR LOCALIZATION USING REFERENCE MAP
Washington State University
Master of Science (MS), Washington State University
01/2021
DOI:
https://doi.org/10.7273/000003129
Handle:
https://hdl.handle.net/2376/119251
Abstract
Autonomous robotic systems are complex robotic systems which are able to complete a task autonomously with no user operation. These systems are increasingly popular in everyday life, manufacturing, health care, and the automotive industry. Autonomous systems can be used to remove operator error, complete complex or dangerous tasks, make everyday life more convenient, and much more. As the need for autonomous systems increases, so does the need for engineers who understand the basic principles of these systems and are able to expound on these principles to fuel innovation. One such principle is robot localization. Robot localization is the robot’s ability to know its own location and orientation relative to its environment. This is a complex problem which involves the use of a sensor/sensors and complex coding. Localization is a vital part of autonomous systems as a robot which is unable to know its position and orientation in its environment can be a major hazard. For example, an autonomous vehicle which is unable to localize in its environment may run into other vehicles, bystanders, or structures. The aim of this research is to develop a platform for LIDAR localization of a simple vehicle which engineering students can use to understand the fundamentals of these highly complex problems. The principles in this paper can be used to design laboratory experiments for undergraduate students.
Presented in this thesis is a simple two-dimensional scan matching approach to localization using a reference map of the vehicle’s environment. This approach expounds upon the previous research performed by Emily Carter and Joel Larson described in the paper titled Fundamental Scan Matching Approach to LIDAR Based Localization. This approach uses a RPLIDAR laser scanner to map the vehicle’s current environment and utilizes two-dimensional scan matching to compare the current environment map to a reference environment map. This scan matching produces the vehicle’s location and orientation within its environment.
Metrics
Details
- Title
- 2-D SCAN-MATCHING APPROACH TO LIDAR LOCALIZATION USING REFERENCE MAP
- Creators
- Emily Carter
- Contributors
- Changki Mo (Advisor)Scott Hudson (Advisor)Joseph Iannelli (Committee Member)
- Awarding Institution
- Washington State University
- Academic Unit
- School of Mechanical and Materials Engineering
- Theses and Dissertations
- Master of Science (MS), Washington State University
- Publisher
- Washington State University
- Number of pages
- 115
- Identifiers
- 99900651899701842
- Language
- English
- Resource Type
- Thesis