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Modified Genetic Algorithm based on A* Algorithm of Multi Objective Optimization for Path Planning

Bashra K. Oleiwi1, Hubert Roth1, and Bahaa I. Kazem2
1.Siegen University/Automatic Control Engineering, Siegen, Germany
2.Mechatronics Engineering,University of Baghdad, Iraq

Abstract—A new hybrid approach algorithm based on modified Genetic Algorithm (GA) and modified the search algorithm (A*) and has been developed to solve the Multi objectives global path planning (MOPP) problem for mobile robot navigation in complex environment with static distributed obstacles. The aim of this combination is to improve GA efficiency and path planning performance. Hence, several genetic operators are proposed based on domain-specific knowledge and characteristics of path planning to avoid falling into a local minimum in complex environment and to improve the optimal path partly such as deletion operator and enhanced mutation with basic A*. In addition, the proposed approach is received an initial population from a classical method or modified A*. The objective function for the proposed approach is to minimizing travelling distance, smoothness and security, without collision with any obstacle in the robot workspace. The simulation results show that the proposed approach is able to achieve multi objective optimization in complex static environment efficiently. Also, it has the ability to find a solution when the environment is complex and the number of obstacles is increasing.  
Index Terms—multi objectives optimization, path planning, mobile robot, static complex environment, GA, A*

Cite: Bashra K. Oleiwi, Hubert Roth, and Bahaa I. Kazem, "Modified Genetic Algorithm based on A* Algorithm of Multi Objective Optimization for Path Planning," Jounal of Automation and Control Engineering, Vol. 2, No. 4, pp. 357-362, December, 2014. doi: 10.12720/joace.2.4.357-362
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