• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.9
• /
• pp.931-938
• /
• 2008

In this paper, a novel localization algorithm robust to the unmodeled systematic odometry errors is proposed for low-cost non-holonomic mobile robots. It is well known that the most pose estimators using odometry measurements cannot avoid the performance degradation due to the dead-reckoning of systematic odometry errors. As a remedy for this problem, we tty to reflect the wheelbase error in the robot motion model as a parametric uncertainty. Applying the Krein space estimation theory for the discrete-time uncertain nonlinear motion model results in the extended robust Kalman filter. This idea comes from the fact that systematic odometry errors might be regarded as the parametric uncertainties satisfying the sum quadratic constrains (SQCs). The advantage of the proposed methodology is that it has the same recursive structure as the conventional extended Kalman filter, which makes our scheme suitable for real-time applications. Moreover, it guarantees the satisfactoty localization performance even in the presence of wheelbase uncertainty which is hard to model or estimate but often arises from real driving environments. The computer simulations will be given to demonstrate the robustness of the suggested localization algorithm.

• The Journal of Korea Robotics Society
• /
• v.9 no.3
• /
• pp.160-169
• /
• 2014

Odometry using wheel encoder is a common relative positioning technique for wheeled mobile robots. The major drawback of odometry is that the kinematic modeling errors are accumulated when the travel distance increases. Therefore, accurate calibration of odometry is required. In several related works, various schemes for odometry calibration are proposed. However, design guidelines of test tracks for odometry calibration were not considered. More accurate odometry calibration results can be achieved by using appropriate test track because the position and orientation errors after the test are affected by the test track. In this paper, we propose the design guidelines of test tracks for odometry calibration schemes using experimental heading errors. Numerical simulations and experiments clearly demonstrate that the proposed design guidelines result in more accurate calibration results.

• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.5
• /
• pp.457-462
• /
• 2005

An empirical way of a covariance matrix which expresses the odometry uncertainty of mobile robots is proposed. This method utilizes PC-method which removes systematic errors of odometry. Once the systematic errors are removed, the odometry error can be modeled using the Gaussian probability distribution, and the parameters of the distribution can be represented by the covariance matrix. Experimental results show that the method yields $5{\%}$ and $2.3{\%}$ offset for the synchro and differential drive robots.

• The Journal of Korea Robotics Society
• /
• v.9 no.1
• /
• pp.39-47
• /
• 2014

Odometry using wheel encoders is one of the fundamental techniques for the pose estimation of wheeled mobile robots. However, odometry has a drawback that the position errors are accumulated when the travel distance increases. Therefore, position errors are required to be reduced using appropriate calibration schemes. The UMBmark method is the one of the widely used calibration schemes for two wheel differential drive robots. In UMBmark method, it is assumed that odometry error sources are independent. However, there is coupled effect of odometry error sources. In this paper, a new calibration scheme by considering the coupled effect of error sources is proposed. We also propose the test track design for the proposed calibration scheme. The numerical simulation and experimental results show that the odometry accuracy can be improved by the proposed calibration scheme.