Autonomous mobile robots navigation using RBF neural compensator

This paper presents an approach to adaptive trajectory tracking of mobile robots which combines a feedback linearization based on a nominal model and a RBF-NN adaptive dynamic compensation. For a robot with uncertain dynamic parameters, two controllers are implemented separately: a kinematics controller and an inverse dynamics controller. The uncertainty in the nominal dynamics model is compensated by a neural adaptive feedback controller. The resulting adaptive controller is efficient and robust in the sense that it succeeds to achieve a good tracking performance with a small computational effort. The analysis of the RBF-NN approximation error on the control errors is included. Finally, the performance of the control system is verified through experiments.

[1]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[2]  Norihiko Adachi,et al.  Adaptive tracking control of a nonholonomic mobile robot , 2000, IEEE Trans. Robotics Autom..

[3]  Shirong Liu,et al.  Dynamic control of a mobile robot using an adaptive neurodynamics and sliding mode strategy , 2004, Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788).

[4]  R. Agarwal,et al.  A linear-interpolation-based controller design for trajectory tracking of mobile robots , 2010 .

[5]  Peng-Yung Woo,et al.  Adaptive exponential stabilization of mobile robots with uncertainties , 1999, Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304).

[6]  Bor-Sen Chen,et al.  Combination of kinematical and robust dynamical controllers for mobile robotics tracking control: (I) optimal H/sub /spl infin// control , 2004, Proceedings of the 2004 IEEE International Conference on Control Applications, 2004..

[7]  Marco H. Terra,et al.  Experimental results on the nonlinear ∞ control via quasi-LPV representation and game theory for wheeled mobile robots , 2009, Robotica.

[8]  Yi Guo,et al.  Dynamic tracking control of uncertain nonholonomic mobile robots , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[9]  Walter Fetter Lages,et al.  MOBILE ROBOT TRAJECTORY TRACKING USING MODEL PREDICTIVE CONTROL , 2005 .

[10]  Indra Narayan Kar,et al.  Design and implementation of an adaptive fuzzy logic-based controller for wheeled mobile robots , 2006, IEEE Transactions on Control Systems Technology.

[11]  R. Carelli,et al.  Dynamic Modeling and Centralized Formation Control of Mobile Robots , 2006, IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics.

[12]  Sauro Longhi,et al.  Learning control of mobile robots using a multiprocessor system , 2006 .

[13]  Tzuu-Hseng S. Li,et al.  EP-based kinematic control and adaptive fuzzy sliding-mode dynamic control for wheeled mobile robots , 2009, Inf. Sci..

[14]  Wanderley Cardoso Celeste,et al.  An adaptive dynamic controller for autonomous mobile robot trajectory tracking , 2008 .

[15]  Erfu Yang,et al.  Nonlinear tracking control of a car-like mobile robot via dynamic feedback linearization , 2004 .

[16]  Ju-Jang Lee,et al.  Design of a robust adaptive controller for a mobile robot , 2000, Proceedings. 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2000) (Cat. No.00CH37113).

[17]  Simon G. Fabri,et al.  Dual Adaptive Control for Trajectory Tracking of Mobile Robots , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[18]  Wei Huo,et al.  Tracking control of wheeled mobile robots with unknown dynamics , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).