Date of Award
2010
Publication Type
Master Thesis
Degree Name
M.Sc.
Department
Computer Science
Keywords
Applied sciences
Supervisor
Dan Wu
Rights
info:eu-repo/semantics/openAccess
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Abstract
Mobile robot localization is the problem of determining the robot's pose given the map of its environment, based on the sensor reading and its movement. It is a fundamental and very important problem in the research of mobile robotics. Grid localization and Monte Carlo localization (MCL) are two of the most widely used approaches for localization, especially the MCL. However each of these two popular methods has its own problems. How to reduce the computation cost and better the accuracy is our main concern. In order to improve the performance of localization, we propose two improved localization algorithms. The first algorithm is called moving grid cell based MCL, which takes advantages of both grid localization and MCL and overcomes their respective shortcomings. The second algorithm is dynamic MCL based on clustering, which uses a cluster analysis component to reduce the computation cost.
Recommended Citation
Wang, Yuefeng, "Two improved methods for mobile robot localization" (2010). Electronic Theses and Dissertations. 8267.
https://scholar.uwindsor.ca/etd/8267