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Robot Path Planning Using Cellular Automata and Genetic Algorithm | ||
| Journal of Advances in Computer Engineering and Technology | ||
| مقاله 3، دوره 5، شماره 1 - شماره پیاپی 17، اردیبهشت 2019، صفحه 19-26 اصل مقاله (596.77 K) | ||
| نوع مقاله: Original Research Paper | ||
| نویسندگان | ||
Zeynab Sedreh  1؛ Mehdi Sadeghzadeh2
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| 1Computer Engineering Department, Dezfoul Branch, Islamic Azad University, Dezfoul, Iran. | ||
| 2Mahshahr Branch, Islamic Azad University, Mahshahr, Iran. | ||
| چکیده | ||
| In path planning Problems, a complete description of robot geometry, environments and obstacle are presented; the main goal is routing, moving from source to destination, without dealing with obstacles. Also, the existing route should be optimal. The definition of optimality in routing is the same as minimizing the route, in other words, the best possible route to reach the destination. In most of the routing methods, the environment is known, although, in reality, environments are unpredictable; But with the help of simple methods and simple changes in the overall program, one can see a good view of the route and obstacles ahead. In this research, a method for solving robot routing problem using cellular automata and genetic algorithm is presented. In this method, the working space model and the objective function calculation are defined by cellular automata, and the generation of initial responses and acceptable responses is done using the genetic algorithm. During the experiments and the comparison we made, we found that the proposed algorithm yielded a path of 28.48 if the lengths of the paths obtained in an environment similar to the other algorithm of 15 / 32, 29.5 and 29.49, which is more than the proposed method. | ||
| کلیدواژه‌ها | ||
| Robot Path Planning؛ Optimization Algorithms؛ Cellular Automata؛ Genetic algorithm؛ Optimal Routing | ||
| مراجع | ||
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[1] Malboobi, M., Khademi, M., AkbarZade Tutunchi, M. and Rajabi Mashhadi, H., 2002. Routing Mobile Robot Using Genetic Algorithm. 10th Iranian conference on electrical engineering (ICEE), Vol.3 [2] Salaki, A. and Kufigar, H., 2014, Comprehensive Robot Motion Optimization Algorithm in the Presence of Obstacles based on Genetic Algorithm. 12th Iranian Conference on Intelligent Systems, Bam Institute of Higher Education [3] Saadatpour, M., Noori Zehmakan, A., Eslahi, M., 2014. Robot routing with the common purpose using cellular automata. First National Conference on Electrical and Computer Engineering in the north of the country, Bandar Anzali, Moj Higher Education Institute. [4] Saniei Abade, M. and Jebel Amelian, Z., 2015. Evolutionary Algorithms and Biosciences. [5] Najafi, N., 2009. Using Multilayer Cellular Automata for Robot Routing. MS, Faculty of Basic Sciences, Shahed University. [6] Masihi, E., Barzinpoor, F., Saedi, S., 2011. Routing a Moving Robot Using a New Method Based on Genetic Algorithm with Variable Variable Length. International Journal of Industrial Engineering and Production Management, University of Science & Technology, Vol. 22, No. 2, Page 100-111 [7] Galcernan, E., Carreras, M., 2013. A Survey on Coverage Path Planning for Robotics. University of Girona Underwater Robotics Research Center (CIRS). [8] Behring, C., Bracho, M., Castro, M. and Moreno, J.A., 2001. An Algorithm for Robot Path Planning with Cellular Automata. Springer-Verlag London Limited, pp 11-19 [9] Chaudhari, Y. and Jena, S., 2016. Global Optimal Path Planning of Mobile Robot Using Genetic Algorithm. International Journal of innovative research in electrical, electronics, instrumentation and control engineering vol.4 , issue 5. [10] Alpap Rashamwala , Deepika P Vinchurkar, 2013 , Robot Path Planning using An Ant Colony Optimization, International Journal Research in Artificial Intelligence (IJARAI),Vol.2 , No.3. [11] Marchese, F., 1996. Cellular Automata in Robot Path Planing. IEEE Conferences, pp. 116-125 [12] Chen, j., Xie, Sh., Li, H., Luo, J. and Feng, k., 2015. Robot path planning based on adaptive integrating of genetic and ant colony algorithm. International journal of innovative computing, information and control, Vol.11, No.3, pp. 833-850. [13] Wang, X.Y., Zhang, G.X., Zhao, G.B., Rong, H.N., Ipate, F. and Lefticaru, R., 2015. A Modified Membrane-Inspired Algorithm Based on Particle Swarm Optimization for Mobile Robot Path Planning. International journal of computers communications & control, Vol.10, No.5, pp. 732-745. | ||
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