Direct and Inverse Neural Modelization of Mobile Robots
In this paper, direct and inverse models determination of a mobile robot using artificial neural networks are proposed. The effectiveness of the proposed algorithm applied to the modeling of behavior of CHAR and KHEPERA robots is verified by simulation experiments. The results of simulation show that the use of the neural networks in the determination of direct model and inverse model is very interesting since it enables to guarantee the time competition and the quality of the modeling.
Copyright © 2015 Praise Worthy Prize - All rights reserved.
A. Garrell and A. Sanfeliu “Model Validation: Robot Behavior in People Guidance Mission using DTM model and Estimation of Human Motion Behavior problem” The IEEE/RSJ International Conference on Intelligent Robots and Systems,Taipei,October 18-22, 2010.
Y. Bassil" Neural Network Model for Path-Planning Of Robotic Rover Systems" International Journal of Science and Technology, Vol. 2, No. 2, 2012.
P. A. Nino-Suarez, E. Aranda-Bricaire and M. Velasco-Villa "Discrete-time sliding mode path-tracking control for a wheeled mobile robot" Proceedings of the 45th IEEE Conference on Decision& Control, San Diego, December 13-15, 2006.
A. Errachdi and M. Benrejeb., "A new algorithm of neural internal model controller using variable learning rate”, International Journal of Neural and Advanced Applications, Volume 1, 2014.
E. Fabrizi, G. Oriolo, S. Panzieri and G. Ulivi, "A KF-based localization algorith for nonholonomic mobile robots”, in 6th IEEE Mediterranean Conference on Control and Automation, pp 130-135.1998.
J. Mo˙zaryn and J. E. Kurek, "Comparison of Neural Network Robot Models with Not Inverted and Inverted Inertia Matrix" W. Duch et al. (Eds.): ICANN, LNCS 3697, pp. 417–422, 2005.
F.L. Lewis, K. Liu and A. Yesildirek, "Neural Net Robot Controller with Guaranteed Tracking Performance". IEEE Transactions on Neural Networks 6, pp. 703-715, 1995.
J. Możaryn J. and E. Kurek, "Calculation of Industrial Robot Model Coefficients Using Neural Networks". Artificial Intelligence and Soft Computing - ICAISC 2004, pp. 792 - 797, 2004.
J. Mo.zaryn and J.E. Kurek, "Neural Network Robot Model with Not Inverted Inertia Matrix". Proc. 10th IEEE Int. Conf. on Methods and Models in Automation and Robotics 2, pp. 1021-1026, 2004.
B. Feng, G. Ma, W.Xie and C. Wang, “Robust tracking control of space robot via neural network”, 1stInternational Symposium on Systems and Control in Aerospace and Astronautics, 2006.
S. Shuzhi, C.C. Ge Hang and L.C. Woon, “Adaptive neural network control of robot manipulators in task space”, IEEE Transactions on Industrial Electronics, 1997.
C. Wang, B. Feng, G. Ma and C. Ma, “Robust tracking control of space robots using fuzzy neural network”, IEEE International Symposium on Computational Intelligence in Robotics and Automation, 2005.
L. Mathew Joseph, “Human-in-the-loop neural network control of a planetary rover on harsh terrain”, Thesis, Georgia Institute of Technology, 2008.
D. Janglová, “Neural Networks in Mobile Robot Motion”, International Journal of Advanced Robotic Systems, Vol. 1, No 1, pp. 15-22, 2004.
M. Peniak, D. Marocco and A. Cangelosi, “Autonomous Robot Exploration Of Unknown Terrain: A Preliminary Model Of Mars Rover Robot”, In Proceedings of 10th ESA Workshop on Advanced Space Technologies for Robotics and Automation, Noordwijk, The Netherlands, 2008.
J. Tani, “Model-based Learning for Mobile Robot Navigation from the Dynamical Systems Perspective”, IEEE Trans. on Syst., Man and Cyb., Vol. 26, No.3, pp. 421-436, 1996.
D. Janglová,"Neural Networks in Mobile Robot Motion", Inernational Journal of Advanced Robotic Systems, Vol 1, No 1, pp. 15-22, 2004.
A. Chatti, I. Ayari, P. Borne and M. Benrejeb, " On the use of neural techniques for path following control of a Car-Like mobile robot", Studies in Informatics and Control, Vol 14, No 4, pp. 221-234, 2005.
M. Vaezi and M. Ali Nekouie, "Adaptive Control of a Robotic Arm Using Neural Networks Based Approach" International Journal of Robotics and Automation, Vo1, Issue: (5), pp. 87-99, 2007.
T. Hester, M. Quinlan and P. Stone, "Generalized Model Learning for Reinforcement Learning on a Humanoid Robot", In IEEE International Conference on Robotics and Automation, 2010.
S. Yildirim, "A proposed neural internal model control for robot manipulators", Journal of Scientific and Industrial Research, Vol 65, pp. 713-720, 2006.
A. Errachdi and M. Benrejeb. "On-line direct inverse neural network control for nonlinear system". 13th STA, International conference on Sciences and Techniques of Automatic control and computer engineering, Monastir, 17-19 December 2012.
A. Errachdi, I. Saad, M. Benrejeb, On-line Identification Method Based on Dynamic Neural Network, (2010) International Review of Automatic Control (IREACO), 3 (5), pp. 474-479.
A. Errachdi, "Contribution to the adaptive neural control of nonlinear discrete systems with variable parameters", Thesis, National Engineering School of Tunis El Manar, Tunisia 2012.
Z.Ghania, "Execution de trajectoire pour robot mobile d’interieur-Réseaux de neuronne", Thesis, University of Batna Faculty of Engineering Sciences, Algeria 2009.
J. Herrera,"Trajectory tracking trough predictive control: application to the Khepera robot", Diploma thesis, 1999.
A.S.P. Niederberger, "Predictive control Design for a Khepera robot: Principles, Simulations and Real-time Implementation", Diploma thesis, February 2002.
M. de K-Team : "Khepera II user manuel". Switzerland, 2002.
L. Amouri-Jamail, "Contribution on the Control and the Reactif Pilot of Wheeled Mobile Robots" Thesis, National Engineering School of Sfax, Tunisia 2012.
B. Hoang Dinh, "Approximation of the inverse kinematics of a robotic manipulator using neural network", Thesis, Heriot-Watt University, 2009.
G. W. Irwin, K. Warwick and K. J. Hunt, "Neural Network Applications inControl". IEE Control Engineering Series 53, 1995.
Karami-Mollaee, A. and Karami-Mollaee, M. R. (2006). A new approach for instantaneous pole placement with recurrent neural networks and its application in control of nonlinear time-varying systems. Syst. Contr. Lett., 55.
A. Errachdi and M. Benrejeb., "A new algorithm for MRAC method using a neural variable learning rate”, International Journal of Neural and Advanced Applications, Volume 1, 2014.
Negadi, K., Mansouri, A., Marignetti, F., Touam, M., An MRAS based estimation method with artificial neural networks for high performance induction motor drives and its experimentation, (2014) International Review of Automatic Control (IREACO), 7 (2), pp. 123-130.
El Kebir, A., Chaker, A., Negadi, K., A neural network controller for a temperature control electrical furnace, (2013) International Review of Automatic Control (IREACO), 6 (6), pp. 689-694.
Mithra Noel, M., Sharma, A., Biologically inspired decentralized target location estimation using neural networks, (2013) International Review of Automatic Control (IREACO), 6 (5), pp. 612-617.
Filippetti, F., Franceschini, G., Ometto, A., Meo, S., Survey of neural network approach for induction machine on-line diagnosis, (1996) Proceedings of the Universities Power Engineering Conference, 1, pp. 17-20.
Filippetti, F., Franceschini, G., Tassoni, C., Meo, S., Ometto, A., Neural network aided on-line diagnostics of induction machine stator faults, (1995) Proceedings of the Universities Power Engineering Conference, 1, pp. 148-151.
Di Stefano, R., Meo, S., Scarano, M., Induction motor faults diagnostic via artificial neural network (ANN), (1994) IEEE International Symposium on Industrial Electronics, pp. 220-225.
- There are currently no refbacks.
Please send any question about this web site to firstname.lastname@example.org
Copyright © 2005-2020 Praise Worthy Prize