Abstract
This paper presented a hierarchical fuzzy path following control scheme based on different fuzzy grain size in a class of unknown environment with static obstacles. By employing fine-grained fuzzy division and design of fuzzy rule table for the rotation angle and speed of a robot, a more accurate path following control was achieved, while more effective fuzzy obstacle avoidance was realized with coarse-grained fuzzy division strategy. The proposed controller was a two-leveled architecture in which the higher level was the decision-making of the sub-task switching of path following or obstacle avoidance, while the lower level was motion control of path following and fuzzy obstacle avoidance. Finally, the simulation experiments were carried out to demonstrate the feasibility and effectiveness of the proposed scheme.
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References
Aicardi M, Cassalino G, Aguiar A, Encarnacao P, Pacsoal A (2001) A planer path following controller for underactuated marine vehicles. In: IEEE mediterranean conference on control and automation, pp 456-465
Do KD, Pan J (2003) State and output-feedback robust path-following controllers for actuated ships using Serret-Frenet. Ocean Eng 31(5–6):587–613
Liu Z, Ding Y, Jiang Y (2011) Following control of four-wheeled mobile robot. J Cent South Univ (Sci Technol) 42(5):1348–1353 (in Chinese)
Yan Z, Chi D, Zhou J, Zhao Z (2012) NGPC-based path following control of UUV. J Huazhong Univ Sic Technol (Nat Sci Ed) 40(5):122–124 (in Chinese)
Vadakkepat P, Miin OC, Peng X, Lee TH (2004) Fuzzy behavior based control of mobile robots. IEEE Trans Fuzzy Syst 12(4):559–564
Cai C, Yang C (2007) A fuzzy-based collision avoidance approach for multi-robot systems. IEEE Int Conf Robot Bio 3:451–459
Wang J, Xiao L (2009) Collision prevention planning of a multi-robot system based on the fuzzy control. Ind Control Appl 28(1):451–459 (in Chinese)
Su W, Meng R, Chong C (2010) A study on soccer robot path planning with fuzzy artificial potential field. Int Conf Comput Control Ind Eng 1:386–390
Cui GQ, Wang Z, Li CS, Ren K (2011) Fuzzy controller for path planning research of mobile robot. IEEE Int Conf Syst Sci Eng Des Manuf Inf 2:319–322
Yuan Y, Jiao J, Cao Z, Zhou C (2011) Fuzzy control coordination based hunting of multiple of multiple autonomous robots. J Huazhong Univ Sci Technol (Nat Sci Ed) 39(II):328–331 (in Chinese)
Qian X, Song A (2012) Path planning for mobile robot based on adaptive fuzzy neural network. J SE Univ (Nat Sci Ed) 42(4):637–642 (in Chinese)
Yang Y, Han F, Cao Z, Tan M, Jin L (2013) Laser sensor based dynamic fitting strategy for obstacle avoidance control and simulation. J Syst Simul 25(4):704–708 (in Chinese)
Acknowldgments
This work is partially supported by the National Natural Science Foundation of China under Grants 61175111 and 61273352.
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Kong, Y., Chen, C., Yang, Y., Cao, Z. (2015). Path Following and Obstacle Avoidance Control Based on Different Fuzzy Grains. In: Deng, Z., Li, H. (eds) Proceedings of the 2015 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 337. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46463-2_7
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DOI: https://doi.org/10.1007/978-3-662-46463-2_7
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