Path Planning Research for Mobile Robot Based on Immune Genetic Algorithm

Q. Wang †, J. Hedner‡

† Network Center of Guangdong Polytechnic Normal University, Guangzhou, 510665, China
‡ Department of Dermatology, Sahlgrenska University Hospital, Gothenburg, Sweden

Cite this paper
Q. Wang, J. Hedner, “Path Planning Research for Mobile Robot Based on Immune Genetic Algorithm”, Journal of Mechanical Engineering Research and Developments, vol. 39, no. 1, pp. 164-172, 2016. DOI: 10.7508/jmerd.2016.01.023

ABSTRACT: Mobile robots have played an important role in many fields, its related technologies research naturally attracted people’s attention. As one of the key technologies of the robot, path planning has been a hot topic for scholars. Therefore, the study of path planning is of great practical significance. Based on this, the immune genetic algorithm and its application in robot path planning are studied in this study. Immune genetic algorithm can be seen as an improved genetic algorithm with immune function. It has been widely used in mechanical optimization design, controllers’ optimization, channel optimization and other fields. For practical problem of mobile robot path planning, an improved immune genetic algorithm – adaptive immune genetic algorithm (AIGA) is proposed in this paper, and is applied in mobile robot dynamic path planning. Besides, the simulation results are analyzed and studied, which show that AIGA is fully capable of performing optimization work of the robot in dynamic environment, and the real-time is strong.

Keywords : Mobile robot; Path planning; Immune genetic algorithm; Dynamic path planning.


[1] B. Zeng, Y. M. Yang, “Method of real-time path planning based on ant colony algorithm in dynamic environment”, Application Research of Computers, vol. 16, no. 3, pp. 860-863, March, 2010.
[2] Z. X. Wu, Y. H. Li, T. Liu, “Research progress and future development on path planning for multi-robot”, Machinery, vol. 19, no. 3, pp. 56-57, March, 2010.
[3] A. J. Cui, “Research on path planning of mobile robot based on genetic algorithm”, Xi’an: Xi’an University of Science and Technology, 2010.
[4] W. W. Min, “Planning and application research on biped robot based on genetic algorithm”, Wuxi: Jiangnan University. 2013.
[5] X. B. Zhang, W. Tong, “Path Planning of Mobile Robot Based on genetic algorithm”, Industrial Control Computer, vol. 26, no. 10, pp. 66-70, October, 2013.
[6] H. Z. Zhou, “Study on Path Planning of Humanoid Robot”, Zhengzhou: Henan Polytechnic University. 2012.
[7] Y. F. Mao, Y. J. Pang, “Application of improved particle swarm optimization in path planning of underwater vehicles”, Journal of Computer Applications, vol. 22, no. 3, pp. 789-792, March, 2013.
[8] H. J. Cui, “Application of improved immune genetic algorithm in combinatorial optimization problems”, Dalian: Dalian Maritime University, 2012.
[9] H. J. Xie, “The implementation of path planning of intelligent robots under dynamic unknown environment”, Shanghai: East China University of Science and Technology, 2010.
[10] B. H. Wang, “Study and future development of mobile robot path planning technology”, Journal of Shenyang Institute of Engineering (Natural Science), vol. 7, no. 4, pp. 348-351, 2013.