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Konferencja
Polish-German Workshop on Dynamical Problems in Mechanical Systems (9 ; 4-10.09.2005 ; Paszkówka, Poland)
Języki publikacji
Abstrakty
This paper deals with a dead reckoning error correction algorithm for a 4-wheel omnidirectional mobile platform. The platform is powered by 4 identical driven and actively steered wheels, which sums up to 8 actuation DOFs. The platform itself is described as unicycle kinematic by 3 DOFs in the horizontal plane containing speed in x- and y direction, and angular velocity around the vertical axis. For estimating the robot's speed the redundancy is solved by an extended Kalman filter, based on a kinematic model of the robot. Dead reckoning based on the estimated robot speed is subject to different systematic and random errors. Over time small errors sum up to large discrepancies between estimated and real robot position, which - especially in office environments with narrow passages in halls and doors - is a big limitation for position estimation based on dead reckoning. Still, dead reckoning offers high resolution position estimation in the close-up range and by data fusion with a landmark-based low resolution position estimation system qualifies for high accuracy path control. In this paper a dead reckoning error correction algorithm is presented, which splits the speed error into one part originating from straight line movement and a second part originating from rotation around the vertical axis. The parameters of the error correction algorithm are estimated by a recursive least squares algorithm. During operation the robot continuously verifies the set of parameters, to account for a drift of parameters due to wear and varying payload of the robot. A significant improvement against simple dead reckoning can be shown.
Czasopismo
Rocznik
Tom
Strony
5--20
Opis fizyczny
Bibliogr. 11 poz., rys., wykr.
Twórcy
Bibliografia
- Abdellatif, H., Michaelsen, A., Heimann, B., 2003, Position estimation and control of an 8-dof omnidirectional mobile robot, in Proc. Of Raad02, 12th Internatinal Workshop on Robotics in Alpe-Adria-Danube Region.
- Alessandri, A., Bartolini, G., Pavanti, P., Punta, E., Vinci, A., 1997, An application of the extended kalman filter for integrated navigation in mobile robotics, in Proc. American Control Conference, 1.
- Borenstein, J., Feng, L., 1994, UMBmark A Method for Measuring, Comparing, and Correcting Dead-reckoning Errors in Mobile Robots, U. of Michigan, Ed. Technical Report, 94, No UMMEAM-94-22.
- Borenstein, J., Feng, L., 1996, Measurement and correction of systematic odometry errors inmobile robots, IEEE Transactions on Robotics and Automation, 12, No 6, 869880.
- Castellanos, J. A., Tards, J. D., 1999, Mobile Robot Localization and Map Building, Kluwer Academic Publishers.
- Congwei Hu, Y. C., Wu Chen, Liu, D., 2003, Adaptive Kalman filtering for vehicle navigation, Journal of Global Positioning Systems, 2, No 1, 42-47.
- Horn, J. P., 1997, Bahnführung eines mobilen Roboters mittels absoluter Lagebestimmung durch Fusion von Entfernungsbild- und Koppelnavigationsdaten, Dissertation, Lehrstuhl für Steuerungs- und Regelungstechnik, Technische Universität München, VDI-Verlag, Düsseldorf.
- Kalman, R. E., 1960, A new approach to linear filtering and prediction problems, Trans. ASME, Series D, Journal of Basic Engineering, 82, 35-45.
- Oriolo, G., Luca, A. D., Vendittelli, M., 2002, Wmr control via dynamic feedback linearization: Design, implementation, and experimental validation, IEEE Transactions on Control Systems Technology, 10, No 6, 835-852.
- Roy, N., Thrun, S., 1999, Online self-calibration for mobile robots, in Proc. of the IEEE/RSJ International Conference on Robotics and Automation (ICRA), Detroit, MI.
- Welch, G., Bishop, G., The Kalman Filter [Online], Available: http://www.cs.unc.edu/~welch/kalman/.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BWA0-0018-0005