Similar articles

Abstract: mobile robot global path planning in a static environment is an important problem. The paper proposes a method of global path planning based on neural network and genetic algorithm. We constructed the neural network model of environmental information in the workspace for a robot and used this model to establish the relationship between a collision avoidance path and the output of the model. Then the two-dimensional coding for the path via-points was converted to one-dimensional one and the fitness of both the collision avoidance path and the shortest distance are integrated into a fitness function. The simulation results showed that the proposed method is correct and effective.

[1] Alexopoulos, C., Griffin, P.M., 1992. Path planning for a mobile robot. IEEE Transactions on Systems, Man and Cybernetics, 22(2):318-322.

[2] Borenstein, J., Koren, Y., 1989. Real-time obstacle avoidance for manipulators and mobile robots. IEEE Transactions on Systems, Man and Cybernetics, 5(19):1179-1187.

[3] Chen, L., Liu, D.Y., 1997. An efficient algorithm for finding a collision-free path among poly obstacles. Journal of Robotics Systems, 7(1):129-137.

[4] Chen, H.H., Du, X., Gu, W.K., 2004. Path planning Method Based on Neural Network and Genetic Algorithm. International Conference on Intelligent Mechatronics and Automation. Sichuan, China, p.667-671.

[5] Dozier, G., McCullough, S., Homaifar, A., Tunstel, E., Moore, L., 1998. Multiobjective Evolutionary Path Planning via Fuzzy Tournament Selection. The 1998 IEEE International Conference on Evolutionary Computation Proceedings. Alaska, p.684-689.

[6] Del, H.A.R., Medrano, M.N., Martin, D.B.B., 2002. A Simple Approach to Robot Navigation Based on Cooperative Neural Networks. IEEE 28th Annual Conference of the Industrial Electronics Society. Spain, p.2421-2426.

[7] Goldberg, D.E., 1989. Genetic Algorithm in Search, Optimization and Machine Learning. Addison-Wesley Publishing Company, Inc., p.23-25.

[8] Khoogar, A.R., Parker, J.K., 1991. Obstacle Avoidance of Redundant Manipulators Using Genetic Algorithms. Proceedings IEEE International Conference on Robotics and Automation. Sacramento, p.317-320.

[9] Noboru, N., Hideo, T., 1997. Path Planning of agricultural mobile robot by neural network and genetic algorithm. Computers and Electronics in Agriculture, 18:187-204.

[10] Ram, A., Arkin, R., Boone, G., 1994. Using genetic algorithms to learn reactive control parameters for autonomous robotic navigation. Adaptive Behavior, 2(3):100-107.

[11] Ramakrishnan, R., Zein-Sabatto, S., 2001. Multiple Path Planning for A Group of Mobile Robots in A 3D Environment Using Genetic Algorithms. Proceedings of IEEE Southeast Con. South Carolina, p.359-363.

[12] Ramakrishnan, R., Zein-Sabatto, S., 2002. Multiple Path Planning for A Group of Mobile Robots in A 2D Environment Using Genetic Algorithms. Proceedings IEEE Southeast Con. Columbia, p.65-71.

[13] Sadati, N., Taheri, J., 2002. Genetic Algorithm in Robot Path Planning Problem in Crisp and Fuzzified Environments. IEEE International Conference on Industrial Technology. Bangkok, Thailand, p.175-180.

[14] Wang, C., Soh, Y.C., Wang, H., 2002. A hierarchical Genetic Algorithm for Path Planning in A Static Environment with Obstacles. IEEE Canadian Conference on Electrical and Computer Engineering, Canada, p.1652-1657.

[15] Woonggie, H., Seungmin, B., Taeyong, K., 1997. Genetic Algorithm Based Path Planning and Dynamic Obstacle Avoidance of Mobile Robots. IEEE International Conference on Computational Cybernetics and Simulation. Orlando, p.2747-2751.

[16] Wu, K.H., Chen, C.H., Lee, J.D., 1996. Genetic-based Adaptive Fuzzy Controller for Robot Path Planning. Proceedings of the Fifth IEEE International Conference on Fuzzy Systems. New Orleans, p.1687-1692.

[17] Zarate, L.E., Becker, M., Garrido, B.D.M., Rocha, H.S.C., 2002. An Artificial Neural Network Structure Able to Obstacle Avoidance Behavior Used in Mobile Robots. IEEE 28th Annual Conference of the Industrial Electronics Society. Spain, p.2457-2461

[18] Zhu, Y., Chang, J., Wang, S., 2002.A New Path-planning Algorithm for Mobile Robot Based on Neural Network. IEEE Region Tenth Conference on Computers, Communications, Control and Power Engineering. Beijing, p.1570-1573.