Hybrid Control Mode Based On Multi-Sensor Information by Fuzzy Approach for Navigation Task of Autonomous Mobile Robot
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Hybrid Control Mode Based On Multi-Sensor Information by Fuzzy Approach for Navigation Task of Autonomous Mobile Robot

Authors: Jonqlan Lin, C. Y. Tasi, K. H. Lin

Abstract:

This paper addresses the issue of the autonomous mobile robot (AMR) navigation task based on the hybrid control modes. The novel hybrid control mode, based on multi-sensors information by using the fuzzy approach, has been presented in this research. The system operates in real time, is robust, enables the robot to operate with imprecise knowledge, and takes into account the physical limitations of the environment in which the robot moves, obtaining satisfactory responses for a large number of different situations. An experiment is simulated and carried out with a pioneer mobile robot. From the experimental results, the effectiveness and usefulness of the proposed AMR obstacle avoidance and navigation scheme are confirmed. The experimental results show the feasibility, and the control system has improved the navigation accuracy. The implementation of the controller is robust, has a low execution time, and allows an easy design and tuning of the fuzzy knowledge base.

Keywords: Autonomous mobile robot, obstacle avoidance, MEMS, hybrid control mode, navigation control.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1100090

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References:


[1] I. Baturone, F.J. Moreno-Velo, V. Blanco and J. Ferruz, “Design of Embedded DSP-Based Fuzzy Controllers for Autonomous Mobile Robots,” IEEE Trans. on Industrial Electronics, Vol. 55, No. 2, pp. 928-936, 2008.
[2] S. Bensalem, M. Gallien, F. Ingrand, I. Kahloul and N. Thanh-Hung, “Designing Autonomous Robots,” IEEE Robotics & Automation Magazine, pp. 67-77, 2009.
[3] G. Yasuda and H. Takai, “Sensor-Based Path Planning and Intelligent teering Control of Nonholonomic Mobile Robots,” Proceedings of the 27th Annual Conference on IEEE Industrial Electronics Society (IECON’01), Denver, CO, USA, pp. 317-322, 2001.
[4] T.-H. Li and S.-J. Chang, “Autonomous fuzzy parking control of a car-like mobile robot,” IEEE Trans. on Systems, Man, and Cybernetics – Part A: Systems and Humans, vol. 33, no. 4, pp. 451-465, 2003.
[5] T.-H. Li, S.-J. Chang and W. Wong, “Fuzzy Target Tracking Control of Autonomous Mobile Robots by Using Infrared Sensors,” IEEE Trans. on Fuzzy Systems, vol. 12, no. 4, pp. 491-501, 2004.
[6] C.H. Hsieh, M.L. Wang, L.W. Kao and H.Y. Lin, “Mobile Robot Localization and Path Planning Using an Omnidirectional Camera and Infrared Sensors,” Proceedings of IEEE International Conference on Systems, Man, and Cybernetics, San Antonio, TX, USA, pp.1947-1952, Oct. 11-14, 2009.
[7] T.A. Riggs, T. Inanc and W. Zhang, “An Autonomous Mobile Robotics Testbed: Construction, Validation, and Experiments,” IEEE Trans. on Control Systems Technology, vol. 18, no. 3, pp. 757-766, 2010.
[8] M. Mucientes, R. Iglesias, C.V. Regueiro, A. Bugarín, P. Cariñena and S. Barro, “Fuzzy Temporal Rules for Mobile Robot Guidance in Dynamic Environments,” IEEE Trans. on Systems, Man, and Cybernetics – Part C: Applications and Reviews, vol. 31, no. 3, pp. 391-398, 2001.
[9] S. Thongchai and K. Kawamura, “Application of Fuzzy Control to a Sonar-Based Obstacle Avoidance Mobile Robot,” Proc. of the IEEE International Conference on Control Applications, Anchorage, Alaska, USA, pp. 425-430, Sep. 25-27, 2000.
[10] J.H. Lilly, “Evolution of a Negative-Rule Fuzzy Obstacle Avoidance Controller for an Autonomous Vehicle,” IEEE Trans. on Fuzzy Systems, vol. 15, no. 4, pp. 718-728, 2007.
[11] C. Rusu, I.T. Birou and E. Szöke, “Fuzzy Based Obstacle Avoidance System for Autonomous Mobile Robot,” 2010 IEEE International Conference on Automation Quality and Testing Roboics (AQTR), Cluj-Napoca, Romania, May 28-30, 2010.
[12] J. Yi, X. Zhang, Z. Ning and Q. Huang, “Intelligent Robot Obstacle Avoidance System Based on Fuzzy Control,” Proc. of the 1st International Conference on Information Science and Engineering (ICISE 2009), Nanjing, China, pp. 3812-3815, Dec. 26-28, 2009.
[13] L. Jiang, B. Liu, X. Chen and H. Zhao, “Research on ODMM Obstacle Avoidance Fuzzy Navigation Based on Ultrasonic-Absolute- Positioning,” Proc. of 2010 International Conference on electrical and Control Engineering, Wuhan, China, pp. 1725-1729, June 25-27, 2010.
[14] S. Duan, Y. Li, S. Chen, L. Chen, L. Zou, Z. Ma and J. Ding, “Study of Obstacle Avoidance Based on Fuzzy Planner for Wheeled Mobile Robot,” Proceedings of the 8th World Congress on Intelligent Control and Automation, Taipei, ROC, pp.672-676, June 21-27, 2011.
[15] S. Wen, W. Zheng, J. Zhu, X. Li and S. Chen, “Elman Fuzzy Adaptive Control for Obstacle Avoidance of Mobile Robots Using Hybrid Force/Position Incorporation,” IEEE Trans. on Systems, Man, and Cybernetics – Part C: Applications and Reviews, vol. 42, no. 4, pp. 603-608, 2012.
[16] H.-D. Kim, S.-W. Seo, I.-h. Jang and K.-B. Sim, “SLAM of Mobile Robot in the indoor Environment with Digital Magnetic Compass and Ultrasonic Sensors,” Proc. of the International Conference on Control, Automation and Systems, Seoul, Korea, pp. 87-90, Oct. 17-20, 2007.
[17] Y.L. Wei and M.C. Lee, “Mobile robot autonomous navigation using MEMS gyro north finding method in Global Urban System,” Proceedings of IEEE International Conference on Mechatronics and Automation, Beijing, China, pp. 91-96, Aug. 7-10, 2011.
[18] Y. Wei and M. Lee, “A New MEMS Gyro North Finding Approach Using LSM for Mobile Robot Steering Detection,” Proc. of SICE Annual Conference, Akita, Japan, pp. 2262-2267, Aug. 20-23, 2012.
[19] S. Park and S. Hashimoto, “Autonomous Mobile Robot Navigation Using Passive RFID in Indoor Environment,” IEEE Trans. on Industrial Electronics, vol. 56, no. (7), pp. 2366-2373, 2009.
[20] S. Han, H.S. Lim, and J.M. Lee, “An Efficient Localization Scheme for a Differential-Driving Mobile Robot Based on RFID System,” IEEE Trans. on Industrial Electronics, vol. 54, no. 6, pp. 3362-3369, 2007.