Stabilization Control of the Differential Mobile Robot Using Lyapunov Function and Extended Kalman Filter

This paper presents the design of a control model to navigate the differential mobile robot to reach the desired destination from an arbitrary initial pose. The designed model is divided into two stages: the state estimation and the stabilization control. In the state estimation, an extended Kalman filter is employed to optimally combine the information from the system dynamics and measurements. Two Lyapunov functions are constructed that allow a hybrid feedback control law to execute the robot movements. The asymptotical stability and robustness of the closed loop system are assured. Simulations and experiments are carried out to validate the effectiveness and applicability of the proposed approach.

[1]  M. Michaek,et al.  Vector-Field-Orientation Feedback Control Method for a Differentially Driven Vehicle , 2010, IEEE Transactions on Control Systems Technology.

[2]  A. Astolfi.  Discontinuous control of nonholonomic systems , 1996 .

[3]  Zhong-Ping Jiang,et al.  Robust exponential regulation of nonholonomic systems with uncertainties , 2000, Autom..

[4]  C. Samson.  Control of chained systems application to path following and time-varying point-stabilization of mobile robots , 1995, IEEE Trans. Autom. Control..

[5]  Marilena Vendittelli,et al.  WMR control via dynamic feedback linearization: design, implementation, and experimental validation , 2002, IEEE Trans. Control. Syst. Technol..

[6]  Keum-Shik Hong,et al.  Adaptive control of an axially moving system , 2009 .

[7]  Jae-Bok Song,et al.  Error recovery framework for integrated navigation system based on generalized stochastic petri nets , 2009 .

[8]  Claude Samson,et al.  Developments in Time-Varying Feedback Stabilization of Nonlinear Systems , 1998 .

[9]  Shuzhi Sam Ge,et al.  Adaptive stabilization of uncertain nonholonomic systems by state and output feedback , 2003, Autom..

[10]  T. T. Hoang,et al.  Multi-sensor perceptual system for mobile robot and sensor fusion-based localization , 2012, 2012 International Conference on Control, Automation and Information Sciences (ICCAIS).

[11]  T. T. Hoang,et al.  Development of an EKF-based localization algorithm using compass sensor and LRF , 2012, 2012 12th International Conference on Control Automation Robotics & Vision (ICARCV).

[12]  Panagiotis Tsiotras,et al.  Controllers for unicycle-type wheeled robots: Theoretical results and experimental validation , 2002, IEEE Trans. Robotics Autom..

[13]  Stergios I. Roumeliotis,et al.  Weighted line fitting algorithms for mobile robot map building and efficient data representation , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[14]  Keum-Shik Hong,et al.  A path following control of an unmanned autonomous forklift , 2009 .

[15]  Feng-Li Lian,et al.  Cooperative Path Planning of Dynamical Multi-Agent Systems Using Differential Flatness Approach , 2008 .

[16]  T. T. Hoang,et al.  Development of a multi-sensor perceptual system for mobile robot and EKF-based localization , 2012, 2012 International Conference on Systems and Informatics (ICSAI2012).

[17]  Zhong-Ping Jiang,et al.  Velocity-Scheduling Control for a Unicycle Mobile Robot: Theory and Experiments , 2009, IEEE Transactions on Robotics.

[18]  Antonio Bicchi,et al.  Closed loop steering of unicycle like vehicles via Lyapunov techniques , 1995, IEEE Robotics Autom. Mag..

[19]  T. T. Hoang,et al.  A novel platform for internet-based mobile robot systems , 2012, 2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA).

[20]  Keum-Shik Hong,et al.  Sonar-based obstacle avoidance using region partition scheme , 2010 .