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A New Approach of Fusion Behavior-Based Fuzzy Control for Mobile Robot Navigation


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DOI: https://doi.org/10.15866/ireaco.v10i1.10390

Abstract


A new fusion approach for a finite number of behaviors for mobile robot is presented. The proposed method can enable multiple behaviors. The degree of activation (DA) of each behavior is handled intelligently to ensure the autonomous navigation of a mobile robot in a dynamic and uncertain environment. Simulation results clearly show the capacity of the new algorithm to manage and merge more than two behaviors at the same time. The general algorithm is based on five fuzzy controllers that will lead the robot to reach a destination from a starting point, while avoiding static and dynamic obstacles, as well as the holes avoidance during its navigation.
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Keywords


Fuzzy Controller; Fusion Behavior; Holes Avoidance; Mobile Robot

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References


F. Cuesta, and A. Ollero, Intelligent mobile robot navigation (Vol. 16 Springer Science & Business Media 2005).
http://dx.doi.org/10.1007/b14079

O. Khatib, Real-time obstacle avoidance for manipulators and mobile robots. The international journal of robotics research, 5(1): 90-98, 1986.
http://dx.doi.org/10.1177/027836498600500106

J. Borenstein and Y. Koren, The vector field histogram-fast obstacle avoidance for mobile robots. IEEE Transactions on Robotics and Automation, 7(3): 278-288, 1991.
http://dx.doi.org/10.1109/70.88137

R. Brooks, A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation, 2(1):14-23, 1986.
http://dx.doi.org/10.1109/jra.1986.1087032

R. C. Arkin, Motor schema—based mobile robot navigation. The International journal of robotics research, 8(4): 92-112, 1989.
http://dx.doi.org/10.1177/027836498900800406

J. M. Watson, D. L. Strayer, Supertaskers: Profiles in extraordinary multitasking ability. Psychonomic bulletin & review, 17(4):479-485. 2010.
http://dx.doi.org/10.3758/pbr.17.4.479

J. K. Rosenblatt, DAMN: A distributed architecture for mobile navigation. Journal of Experimental & Theoretical Artificial Intelligence, 9(2-3): 339-360, 1997.
http://dx.doi.org/10.1080/095281397147167

Moussaoui, R., Medroumi, H., Moutaouakkil, F., Design and Modeling of SMA Architecture Using MaSE Methodologies, (2014) International Review on Computers and Software (IRECOS), 9 (1), pp. 74-79.

Ali, A., Wahid, N., Said, B., Fuzzy Logic Controller Optimization Based on PSO and BBO for Quadruple Tank System, (2015) International Review on Modelling and Simulations (IREMOS), 8 (5), pp. 540-549.
http://dx.doi.org/10.15866/iremos.v8i5.7634

C. C. Lee, Fuzzy logic in control systems: fuzzy logic controller. II. IEEE Transactions on Systems, Man and Cybernetics , 20(2): 419-435, 1990.
http://dx.doi.org/10.1109/21.52552

D. H. Zhai and Y. Xia, Adaptive fuzzy control of multilateral asymmetric teleoperation for coordinated multiple mobile manipulators. IEEE Transactions on Fuzzy Systems, 24(1): 57-70. 2016.
http://dx.doi.org/10.1109/tfuzz.2015.2426215

W. L. Baker, and J. A. Farrell, An introduction to connectionist learning control systems. Handbook of Intelligent Control, vol.2: 35-64, 1992.
http://dx.doi.org/10.1117/12.25211

Mahmoud, I., Errachdi, A., Benrejeb, M., Direct and Inverse Neural Modelization of Mobile Robots, (2015) International Review of Automatic Control (IREACO), 8 (2), pp. 86-93.
http://dx.doi.org/10.15866/ireaco.v8i2.4595

R. K. Panda and B. B. Choudhury An Effective Path Planning of Mobile Robot Using Genetic Algorithm. In IEEE International Conference on Computational Intelligence & Communication Technology (CICT), pp. 287-291, February 2015.
http://dx.doi.org/10.1109/cict.2015.145

Ramesh, K., Baskar, N., Pandianathan, A., Optimization of Sheet Metal Parts Nesting Using Genetic Algorithm, (2014) International Review of Mechanical Engineering (IREME), 8 (4), pp. 810-815.

Taki El-Deen, A., Mahmoud, A., R. El-Sawi, A., Optimal PID Tuning for DC Motor Speed Controller Based on Genetic Algorithm, (2015) International Review of Automatic Control (IREACO), 8 (1), pp. 80-85.
http://dx.doi.org/10.15866/ireaco.v8i1.4839

Bouchiba, F., Wahid, N., Neuro-Fuzzy Navigation of a Mobile Robot in an Unknown Environment, (2015) International Review of Automatic Control (IREACO), 8 (3), pp. 220-227.
http://dx.doi.org/10.15866/ireaco.v8i3.6102

B. González, F. Valdez, P. Melin and G. Prado-Arechiga, Fuzzy logic in the gravitational search algorithm for the optimization of modular neural networks in pattern recognition. Expert Systems with Applications, 42(14): 5839-5847, 2015.
http://dx.doi.org/10.1016/j.eswa.2015.03.034

F. Boufera, F. Debbat, F. Mondada and M. F. Khelfi, Fuzzy control system for autonomous navigation of Thymio II mobile robots. Journal of Emerging Technologies in Web Intelligence, 6(1):101-105, 2014.
http://dx.doi.org/10.4304/jetwi.6.1.101-105

Osuský, J., Kralev, J., Slavov, T., Robust Position Control for Two Wheels Mobile Robotic System, (2015) International Review of Automatic Control (IREACO), 8 (4), pp. 267-271.
http://dx.doi.org/10.15866/ireaco.v8i4.7046

A. Fatmi, A. A. Yahmadi, L. Khriji, and N. Masmoudi, A fuzzy logic based navigation of a mobile robot. World academy of science, Engineering and Technology, vol. 22:169-174, 2006.
http://dx.doi.org/10.1155/2016/9548482

M. Wang, and J. N. Liu, Fuzzy logic-based real-time robot navigation in unknown environment with dead ends. Robotics and Autonomous Systems,56(7): 625-643,2008.
http://dx.doi.org/10.1016/j.robot.2007.10.002

H. R. Hassanzadeh, M. R. Akbarzadeh-T, A. Akbarzadeh and A. Rezaei, An interval-valued fuzzy controller for complex dynamical systems with application to a 3-PSP parallel robot. Fuzzy Sets and Systems, vol. 235: 83-100, 2014.
http://dx.doi.org/10.1016/j.fss.2013.02.009

F. Abdessemed, K. Benmahammed and E. Monacelli, A fuzzy-based reactive controller for a non-holonomic mobile robot. Robotics and autonomous Systems, 47(1): 31-46, 2004.
http://dx.doi.org/10.1016/j.robot.2004.02.006

Seddjar, A., Berrached, N., A Fuzzy Approach for a Hybrid Multi-Mobile Robot Control Architecture to Maintain a Specific Formation During Navigation, (2015) International Review of Automatic Control (IREACO), 8 (1), pp. 63-71.
http://dx.doi.org/10.15866/ireaco.v8i1.5098

O. R. E. Motlagh, T. S. Hong and N. Ismail, Development of a new minimum avoidance system for a behavior-based mobile robot. Fuzzy Sets and Systems, 160(13):1929-1946, 2009.
http://dx.doi.org/10.1016/j.fss.2008.09.015

D. Xu, X. Zhang, Z. Zhu, C. Chen and P. Yang, Behavior-Based Formation Control of Swarm Robots. Mathematical Problems in Engineering, 2014.
http://dx.doi.org/10.1155/2014/205759

Madevan, B., Sudhagar, K., Rajarajeswari, G., Navigational Intelligence of an Autonomous Mobile Robot participating in an Agent Based Architecture co-ordinates, (2014) International Review of Mechanical Engineering (IREME), 8 (4), pp. 742-749.

B. ELKARI, H. Ayad and A. ELkari, Behavior architecture fuzzy controller for unicycle robot. IEEE International Conference on Multimedia Computing and Systems (ICMCS), pp. 728-733. April 2014.
http://dx.doi.org/10.1109/icmcs.2014.6911317

L.E. Dubins, On Curves of Minimal Length with a Constraint on Average Curvature, and with Prescribed Initial and Terminal Positions and Tangents, American Journal of Mathematics 79 (3): 497–516. (July 1957).
http://dx.doi.org/10.2307/2372560


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