Path Planning of Intelligent Mobile Robot Using Modified Genetic Algorithm
Nadia Adnan Shiltagh1, Lana Dalawr Jalal2
1Nadia Adnan Shiltagh, Computer Engineering, University of Baghdad, Baghdad, Iraq.
2Lana Dalawr Jalal, Electrical Department, Faculty of Engineering, University of Sulaimani, Sulaimani, Kurdistan Region, Iraq.
Manuscript received on April 03, 2013. | Revised Manuscript received on April 27, 2013. | Manuscript published on May 05, 2013. | PP: 31-36 | Volume-3, Issue-2, May 2013. | Retrieval Number: B1421053213/2013©BEIESP
Open Access | Ethics and Policies | Cite
© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: One aspect of interest in robotics is planning the optimal path for a mobile robot. The objective of path planning is to determine the shortest feasible path with the minimum time required for mobile robots to move from a starting position to a target position. In this study, Modified Genetic Algorithm (MGA) is developed for a global path planning, and the application of MGA to the problem of mobile robot navigation is investigated under an assumption that an environment model has been established already. The proposed algorithm read the map of the working environment which expressed by grid model and then creates an optimal or near optimal collision free path. The MGA algorithm was simulated using MATLAB R2012a. Adaptive population size without selection and mutation operators are used in the proposed algorithm. The simulation results demonstrate that this algorithm has a great potential to solve the path planning with satisfactory results in terms of minimizing distance and execution time.
Keywords: Global path planning, intelligent mobile robot, modified genetic algorithm, optimal path.