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An Improved Path Planning Method Based on Artificial Potential Field for a Mobile Robot


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1. Rimon, E., D. E. Koditschek. Exact Robot Navigation Using Artificial Potential Functions. - IEEE Trans. on Robotics and Automation, Vol. 8, 1992, pp. 529-551.10.1109/70.163777Search in Google Scholar

2. Vadakkepat, P., K. C. Tan, W. Ming-Liang. Evolutionary Artificial Potential Fields and Their Application in Real Time Robot Path Planning. - In: Proc. of 2000 Congress on Evolutionary Computation, 16-19 July 2000.Search in Google Scholar

3. Qixin, C., H. Yanwen, Z. Jingliang. An Evolutionary Artificial Potential Field Algorithm for Dynamic Path Planning of Mobile Robot. - In: Proc. of International Conference on Intelligent Robots and Systems(IEEE/RSJ), 9-15 October 2006.10.1109/IROS.2006.282508Search in Google Scholar

4. Khatib, O. Real-Time Obstacle Avoidance for Manipulators and Mobile Robots. - In: Proc. of International Conference on Robotics and Automation, 25-28 March 1990.Search in Google Scholar

5. Revello, T. E., R. McCartney. A Cost Term in an Evolutionary Robotics Fitness Function. - In: Proc. of Congress on Evolutionary Computation, 2000.Search in Google Scholar

6. Ge, S. S., Y. J. Cui. New Potential Functions for Mobile Robot Path Planning. - Trans. on Robotics and Automation, Vol. 16, 2000, No 5, pp. 615-621.10.1109/70.880813Search in Google Scholar

7. Agirrebeitia, J., et al. A New APF Strategy for Path Planning in Environments with Obstacles. - Mechanism and Machine Theory, Vol. 40, 2005, pp. 645-658.10.1016/j.mechmachtheory.2005.01.006Search in Google Scholar

8. Shi, H., Z. Chen, C. Sun. Application of Chaotic Optimization Algorithm to Problems with Motion Planning for Mobile Robots. - In: Proc. of 2003 IEEE International Conference on Robotics, Intelligent Systems and Signal Processing, October 2003.Search in Google Scholar

9. Motlagh, O. R. E., T. S. Hong, N. Ismail. Development of a New Minimum Avoidance System for a Behavior-Based Mobile Robot. - Fuzzy Sets and Systems, Vol. 160, 2008, pp. 1929-1946.10.1016/j.fss.2008.09.015Search in Google Scholar

10. La, Y. L., S. Hong, J. Huang. The New Environment Model Building Method of Penetration Mission Based on the Artificial Potential Field Approach. - In: Proc. of 2012 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support, 2012.Search in Google Scholar

11. Fathy, E., K. El-Metwally, A. R. Hanafy. Multi-Robot Tracking of Multiple Moving Targets Using Potential Field Approach. - In: Proc. of International Symposium on Innovations in Intelligent Systems and Applications, 2010.Search in Google Scholar

12. Lorenz, E. N. Deterministic Non-Periodic Flow. - Journal of the Atmospheric Sciences, Vol. 20, 1963, No 2, pp. 130-141.10.1175/1520-0469(1963)020<0130:DNF>2.0.CO;2Search in Google Scholar

13. Yang, D., G. Li, G. Cheng. On the Efficiency of Chaos Optimization Algorithms for Global Optimization. - Chaos, Solitons and Fractals, Vol. 34, 2007, pp. 1366-1375.10.1016/j.chaos.2006.04.057Search in Google Scholar

14. Borenstein, J., Y. Koren. Real-Time Obstacle Avoidance for Fast Mobile Robots. - IEEE Trans. Syst., Man, Cybern., Vol. 19, 1989, No 9, pp. 1179-1187.10.1109/21.44033Search in Google Scholar

15. Koren, Y., J. Borenstein. Potential Field Methods and Their Inherent Limitations for Mobile Robot Navigation. - In: Proc. of IEEE Conf. Robotics and Automation, Sacramento, 7-12 April 1991.Search in Google Scholar

16. Kh o a, T. Q. D., M. Nakagawa. Training Multilayer Neural Network by Global Chaos Optimization Algorithms. - In: Proc. of Int. Joint Conf. on Neural Networks (IJCNN’2007), August 2007.10.1109/IJCNN.2007.4370944Search in Google Scholar

17. Shi, H., Z. Chen, C. Sun. Path Planning Method for Robot Based on Chaotic Optimization Algorithm. - Robot, Vol. 27, 2005, No 2, pp. 153-157.Search in Google Scholar

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Temas de la revista:
Computer Sciences, Information Technology