Path Planning For A Mobile Robot Using Ant Colony Optimization

• Main Authors: Peng, Cisiang, 彭啟翔
• Other Authors: Chang, Chiader
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/33325901616048423018

碩士 === 明志科技大學 === 電機工程研究所 === 100 === Abstract This thesis aims to find an optimal path planning strategy for mobile robot by using the Ant Colony Optimization (ACO) algorithms. First, the obstacle existed between the starting point and the end point in a known environment is recognized, then apply the ACO to search optimal path with the capability to avoid collision with the obstacle for a mobile robot. From comparisons between the ACO algorithms and the Genetic Algorithms (GA), it can be found that the ACO algorithms provide better convergence in searching the optimal path. The Sentinel Robot and Constellation Navigated System are combined to confirm the simulated path planning solution, and ensure the robot to move according to the optimal path correctly and demonstrate the ability to avoid the obstacle smoothly. The goal of economizing the energy consumption and enhancing the searching efficiency of an optimal path for a mobile robot can then be reached. Keywords: Ant colony optimization, Genetic algorithms, optimal path planning, mobile robot.