- Volume 20 Issue 4
DOI QR Code
Effective Robot Path Planning Method based on Fast Convergence Genetic Algorithm
유전자 알고리즘의 수렴 속도 향상을 통한 효과적인 로봇 길 찾기 알고리즘
- Seo, Min-Gwan (Dept. of Computer Science, Chung-Ang University) ;
- Lee, Jae-Sung (Dept. of Computer Science, Chung-Ang University) ;
- Kim, Dae-Won (Dept. of Computer Science, Chung-Ang University)
- Received : 2015.02.02
- Accepted : 2015.02.24
- Published : 2015.04.30
The Genetic algorithm is a search algorithm using evaluation, genetic operator, natural selection to populational solution iteratively. The convergence and divergence characteristic of genetic algorithm are affected by selection strategy, generation replacement method, genetic operator when genetic algorithm is designed. This paper proposes fast convergence genetic algorithm for time-limited robot path planning. In urgent situation, genetic algorithm for robot path planning does not have enough time for computation, resulting in quality degradation of found path. Proposed genetic algorithm uses fast converging selection strategy and generation replacement method. Proposed genetic algorithm also uses not only traditional crossover and mutation operator but additional genetic operator for shortening the distance of found path. In this way, proposed genetic algorithm find reasonable path in time-limited situation.
Grant : 뮤직 맵: 메타 정보 상관성 도출 및 시각화 기술을 이용한 음악 추천 서비스 개발
- S. Koenig, M. Likhachev, and D. Furcy, "Lifelong planning A*", Artif. Intell. Vol. 155, No. 1, pp. 93-146, May 2004. https://doi.org/10.1016/j.artint.2003.12.001
- A. Stentz, "Optimal and efficient path planning for partially-known environments", Proc. IEEE Conf. Robotics and Automation, pp. 3310-3317, San Diego, USA, May 1994.
- H. Liu, N. Stoll, S. Junginger, and K. Thurow, "A Floyd-genetic algorithm based path planning system for mobile robots in laboratory automation", Proc. IEEE Int. Conf. Robotics and Biomimetics, pp. 1550-1555, Guangzhou, China, Dec. 2012
- Q. Li,, W. Zhang, Y. Yin, Z. Wang, and G. Liu, "An improved genetic algorithm of optimum path planning for mobile robots", Proc. Int. Conf. Intelligent Systems Design and Applications, pp. 637-642, Jinan, China, Sept. 2013.
- C. Tsai, H. Huang, and C. Chan, "Parallel elite genetic algorithm and its application to global path planning for autonomous robot navigation". IEEE Trans. Ind. Electron, Vol. 58, No. 10, pp. 4813-4821, Jan. 2011. https://doi.org/10.1109/TIE.2011.2109332
- M. Naderan-Tahan, and M. Manzuri-Shalmani, "Efficient and safe path planning for a mobile robot using genetic algorithm", Proc. IEEE Congr. Evolutionary Computation, pp. 2091-2097, Trondheim, Norway. May 2009.
- S.G. Cui, and J.L. Dong, "Detecting robots path planning based on improved genetic algorithm", Proc. Int. Conf. Instrumentation, Measurement, Computer, Communication and Control, pp. 204-207, Shenyang, China, Sept. 2013.
- J.H. Kim, Y.H. Kim, S.H. Choi, and I.W. Park, "Evolutionary multi-objective optimization in robot soccer system for education", IEEE Comput. Intell. Mag., Vol. 4, No. 1, pp. 31-41, Jan. 2009. https://doi.org/10.1109/MCI.2008.930985
- S. Tachi, and K. Komoriya, "Guide dog robot", Autonomous Mobile Robots: Control, Planning, and Architecture, pp. 360-367, 1984.
- J.M. Johnson, V. Rahmat-Samii, Venetic algorithms in engineering electromagnetics". IEEE Antennas and Propagation Magazine, Vol. 39, No. 4, pp. 7-21, Aug. 1997. https://doi.org/10.1109/74.632992
- M. Srinivas, and L.M. Patnaik, "Genetic algorithms: A survey", Computer, Vol. 27, No. 6, pp. 17-26, June. 1994. https://doi.org/10.1109/2.294849
- A. Tuncer, and M. Yildirim, "Dynamic path planning of mobile robots with improved genetic algorithm", Comput. Electr. Eng., Vol. 38, pp. 1564-1572, Nov. 2012. https://doi.org/10.1016/j.compeleceng.2012.06.016
- M. Davoodi,, F. Panahi, A. Mohades, and S. N. Hashemi, "Multi-objective path planning in discrete space", Appl. Soft Comput., Vol. 13, No. 1, pp. 709-720, Jan. 2013. https://doi.org/10.1016/j.asoc.2012.07.023
- Y. Hu, and S. Yang, "A knowledge based genetic algorithm for path planning of a mobile robot", Proc. IEEE Int. Conf. Robotics and Automation, pp. 4350-4355, New Orleans, USA, May 2004.
- M. Gemeinder, and M. Gerke, "GA-based path planning for mobile robot systems employing an active search algorithm", Appl. Soft Comput., Vol. 3, No. 2, pp. 149-158, Sept. 2003. https://doi.org/10.1016/S1568-4946(03)00010-3
- J. Lee, B.Y. Kang, and D.W. Kim, "Fast genetic algorithm for robot path planning", Electr. Lett., Vol. No. 23, pp. 1449-1451, Nov. 2013.
- M. Samadi, and M.F. Othman, "Global Path Planning for Autonomous Mobile Robot using Genetic Algorithm", Proc. Int. Conf. Signal-Image Technology & Internet-Based Systems, pp. 726-730, Kyoyo, Japan, Dec. 2013.