Document Type
Conference Item
Publication Date
9-1-2011
Abstract
Mobile Robot Navigation is an advanced technique where static, dynamic, known and unknown environment is involved. In this research, Genetic Algorithm (GA) is used to assist mobile robot to move, identify the obstacles in the environment, learn the environment and reach the desired goal in an unknown and unrecognized environment. This study is focused on exploring the algorithm that avoids acute obstacles in the environment. In the event of mobile robot encountering any dynamic obstacles when travelling from the starting position to the desired goal according to the optimum collision free path determined by the controller, the controller is capable of replanning the new optimum collision free path. MATLAB simulation is developed to verify and validate the algorithm before they are real time implemented on Team AmigoBotTM robot. The results obtained from both simulation and actual application confirmed the flexibility and robustness of the controllers designed in path planning.
Keywords
Genetic Algorithm (GA), Genetic Controller, Genetic Algorithm (GA) based Dynamic Path Planning Algorithm (DPPA), Team AmigoBotTM robot and MATLAB.
Divisions
fac_eng
Event Title
2011 IEEE Symposium on Industrial Electronics and Applications, ISIEA 2011
Event Location
Langkawi
Event Dates
25-28 Sep 2011
Event Type
conference