Localization of a wheeled mobile robot by sensor data fusion based on a fuzzy logic adapted Kalman filter

Abstract Accurate estimates of mobile robot location, if available, can be used to improve the performance of a vehicle dynamics control system. To this purpose, the data provided by odometric and sonar sensors are here fused together by means of an extended Kalman filter, providing robot position and orientation estimates at each sampling instant. To cope with the tracking of long trajectories, the performance of the filter is improved by introducing an on-line fuzzy-rule-based adaptation scheme.

[1]  Giuseppe Oriolo,et al.  Local incremental planning for nonholonomic mobile robots , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[2]  James L. Crowley,et al.  World modeling and position estimation for a mobile robot using ultrasonic ranging , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[3]  J. Lalk.  Intelligent adaptation of Kalman filters using fuzzy logic , 1994, Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference.

[4]  Ingemar J. Cox,et al.  Blanche-an experiment in guidance and navigation of an autonomous robot vehicle , 1991, IEEE Trans. Robotics Autom..

[5]  Hugh F. Durrant-Whyte,et al.  Mobile robot localization by tracking geometric beacons , 1991, IEEE Trans. Robotics Autom..

[6]  Fernando Figueroa,et al.  A Robust Navigation System for Autonomous Vehicles using Ultrasonics , 1993 .

[7]  Sauro Longhi,et al.  Development and Experimental Validation of an Adaptive Estimation Algorithm for the On-Line Localization of Mobile Robots by Multisensor Fusion , 1997 .

[8]  Chih-Ming Wang.  Location Estimation and Uncertainty Analysis for Mobile Robots , 1990, Autonomous Robot Vehicles.

[9]  Marie-José Aldon,et al.  Mobile robot attitude estimation by fusion of inertial data , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[10]  Roman Kuc,et al.  A Physically Based Navigation Strategy for Sonar-Guided Vehicles , 1991, Int. J. Robotics Res..

[11]  Kajiro Watanabe,et al.  Fuzzy Logic Rule-Based Kalman Filter for Estimating True Speed of A Ground Vehicle , 1995, Intell. Autom. Soft Comput..

[12]  Essameddin Badreddin,et al.  Mobile robot localization in a structured environment cluttered with obstacles , 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

[13]  Kostas J. Kyriakopoulos,et al.  Sensor-based self-localization for wheeled mobile robots , 1995, J. Field Robotics.

[14]  Michael Drumheller,et al.  Mobile Robot Localization Using Sonar , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  John J. Leonard,et al.  Directed Sonar Sensing for Mobile Robot Navigation , 1992 .

[16]  Ger Honderd,et al.  Wall-following control of a mobile robot , 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

[17]  Sauro Longhi,et al.  Development and experimental validation of an adaptive extended Kalman filter for the localization of mobile robots , 1999, IEEE Trans. Robotics Autom..

[18]  Ph. Bonnifait,et al.  6 DOF Dynamic Localization of a Mobile Robot Using Odometry, Inclinometers and a Goniometric System , 1997 .