Research on Path Planning for Mobile Robot Based on Grid and Hybrid of GA/SA

Path planning is the kernel problem of the robot technology area. In this paper, the grid method is used to make environmental modeling, Since the Genetic Algorithm (GA) has its immanent limitations and the Simulated Annealing (SA) Algorithm has the advantages in some aspects, combined these two algorithms together just achieve the perfection. In view of this, a hybrid of GA and SA (GA-SA Hybrid) is proposed in this paper to solve path planning problem for mobile robot. The algorithm making the crossover and mutation probability adjusted adaptively and nonlinearly with the completion time, can avoid such disadvantages as premature convergence. The new algorithm has better capability of searching globally and locally. The simulation results demonstrate that the proposed algorithm is valid and effective.

[1]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[2]  Ying Zhang,et al.  A rough set GA-based hybrid method for robot path planning , 2006, Int. J. Autom. Comput..

[3]  Hong Bing-rong A Knowledge Based Genetic Algorithm for Path Planning of a Mobile Robot , 2006 .

[4]  Simon X. Yang,et al.  A knowledge based genetic algorithm for path planning of a mobile robot , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[5]  Mitsuo Gen,et al.  A hybrid genetic and variable neighborhood descent algorithm for flexible job shop scheduling problems , 2008, Comput. Oper. Res..

[6]  Ching-Lai Hwang,et al.  Multiple Attribute Decision Making: Methods and Applications - A State-of-the-Art Survey , 1981, Lecture Notes in Economics and Mathematical Systems.