Relative localization using path odometry information
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All mobile bases suffer from localization errors. Previous approaches to accommodate for localization errors either use external sensors such as lasers or sonars, or use internal sensors like encoders. An encoder’s information is integrated to derive the robot’s position; this is called odometry. A combination of external and internal sensors will ultimately solve the localization error problem, but this paper focuses only on processing the odometry information. We solve the localization problem by forming a new odometry error model for the synchro-drive robot then use a novel procedure to accurately estimate the error parameters of the odometry error model. This new procedure drives the robot through a known path and then uses the shape of the resulting path to estimate the model parameters. Experimental results validate that the proposed method precisely estimates the error parameters and that the derived odometry error model of the synchro-drive robot is correct.
KeywordsRelative localization Mobile robot Odometry error model Odometry calibration Synchro-drive robot Differential drive robot Generalized voronoi graph
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- Beer, F.P. and Johnston, E.R. 1994. Vector mechanics for engineers. McGraw Hill, pp. 344–345.Google Scholar
- Borenstein, J. and Feng, L. 1996b. Gyrodometry: A new method for combining data from gyros and odometry in mobile robots. International Conference on Robotics and Automation, 423–428.Google Scholar
- Duckett, D., Marsland, S., and Shapiro, J. 2000. Learning globally consistent maps by relaxation. International Conference on Robotics and Automation, 3841–3846.Google Scholar
- Kim, M.C., Chung, W.K., and Youm. Y. 1999. Posture estimation of car-like mobile robot using disturbance conditions. Advanced Robotics, 13(2):189–202.Google Scholar
- Kim, S.B., Choi, K., Lee, S., Choi, J., Hwang, T., Jang, B., and Lee, J. 2004. A bimodal approach for land vehicle localization. ETRI Journal, 26(5):497–500.Google Scholar
- Larsen, T.D., Bak, M., Andersen, N.A., and Ravn, O. 1998. Location estimation for autonomously guided vehicle using an augmented kalman filter to autocalibrate the odometry. FUSION 98, Spie conference Las Vegas.Google Scholar
- Martinelli, A., Tomatis, N., Tapus, A., and Siegwart, R. 2003. Simultaneous localization and odometry calibration for mobile robot. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, 1499–1504.Google Scholar
- Murata, S. and Hirose, T. 1993. Onboard locating system using real-time image processing for a self-navigating vehicle. IEEE Trans. on Industrial Electronics, 40(1):145–154.Google Scholar
- Roy, N. and Thrun, S. 1999. Online self-calibration for mobile robots. International Conference on Robotics and Automation, 2292–2297.Google Scholar
- Wang, C.M. 1988. Location estimation and uncertainty analysis for mobile robots. International Conference on Robotics and Automation, 1230–1235.Google Scholar