Fuzzy logic based nonlinear Kalman filter applied to mobile robots modelling

In order to reduce the false alarms in fault detection systems for mobile robots, accurate state estimation is needed. Through this work, a new method for localization of a mobile robot is presented. First, a Takagi-Sugeno fuzzy model of a mobile robot is determined, which is optimized using genetic algorithms, creating a precise representation of the kinematic equations of the robot. Then, the fuzzy model is used to design a new extension of the Kalman filter, based on several linear Kalman filters. Finally, the fuzzy filter is compared to the conventional extended Kalman filter, showing an improvement over the estimation made. The fuzzy filter also presents advantages in implementation, due to the fact that the covariance matrices needed are easier to estimate, increasing the estimation frequency.

[1]  Jurek Z. Sasiadek,et al.  ADAPTIVE FUZZY LOGIC SYSTEM FOR SENSOR FUSION IN DEAD-RECKONING MOBILE ROBOT NAVIGATION , 2002 .

[2]  Hartmut Surmann,et al.  A Genetic Algorithm for Structural and Parametrical Tuning of Fuzzy Systems , 1999 .

[3]  Ole Ravn,et al.  Design of Kalman filters for mobile robots; evaluation of the kinematic and odometric approach , 1999, Proceedings of the 1999 IEEE International Conference on Control Applications (Cat. No.99CH36328).

[4]  Jorge Angeles,et al.  Fundamentals of Robotic Mechanical Systems: Theory, Methods, and Algorithms , 1995 .

[5]  T. Başar,et al.  A New Approach to Linear Filtering and Prediction Problems , 2001 .

[6]  Zengqi Sun,et al.  Analysis and design of fuzzy controller and fuzzy observer , 1998, IEEE Trans. Fuzzy Syst..

[7]  Dr. Rainer Palm,et al.  Model Based Fuzzy Control , 1997, Springer Berlin Heidelberg.

[8]  Stergios I. Roumeliotis,et al.  Extended Kalman filter for frequent local and infrequent global sensor data fusion , 1997, Other Conferences.

[9]  C. S. George Lee,et al.  Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems , 1996 .

[10]  Sung Hoon Jung,et al.  Queen-bee evolution for genetic algorithms , 2003 .

[11]  Han Wang,et al.  Fuzzy logic Kalman filter estimation for 2-wheel steerable vehicles , 1999, Proceedings 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human and Environment Friendly Robots with High Intelligence and Emotional Quotients (Cat. No.99CH36289).

[12]  Liqiang Feng,et al.  Measurement and correction of systematic odometry errors in mobile robots , 1996, IEEE Trans. Robotics Autom..