Date of Award
2017
Publication Type
Master Thesis
Degree Name
M.Sc.
Department
Computer Science
Keywords
Ant colony optimization; Grid Method; Robot Path Planning
Supervisor
Wu, Dan
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
The path planning for mobile robots is one of the core contents in the field of robotics research with complex, restrictive and nonlinear characteristics. It consists of automatically determining a path from an initial position of the robot to its final position. Due to classic approaches have several drawbacks, evolutionary methods such as Ant Colony Optimization Algorithm (ACA) and Genetic Algorithm (GA) are employed to solve the path planning efficiently.
Recommended Citation
Wang, Chenhan, "Comparative Research on Robot Path Planning Based on GA-ACA and ACA-GA" (2017). Electronic Theses and Dissertations. 7403.
https://scholar.uwindsor.ca/etd/7403