Tracking and data association
Directed Sonar Sensing for Mobile Robot Navigation
Directed Sonar Sensing for Mobile Robot Navigation
Correction of systematic odometry errors in mobile robots
IROS '95 Proceedings of the International Conference on Intelligent Robots and Systems-Volume 3 - Volume 3
International Journal of Robotics Research
Consistent triangulation for mobile robot localization using discontinuous angular measurements
Robotics and Autonomous Systems
Calibration for mobile robots with an invariant Jacobian
Robotics and Autonomous Systems
Dynamic motion modelling for legged robots
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Mobile robot self-diagnosis with a bank of adaptive particle filters
ICAIS'11 Proceedings of the Second international conference on Adaptive and intelligent systems
Improving odometry using a controlled point laser
Autonomous Robots
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This paper presents both the theory and the experimental results of a method allowing simultaneous robot localization and odometry error estimation (both systematic and non-systematic) during the navigation. The estimation of the systematic components is carried out through an augmented Kalman filter, which estimates a state containing the robot configuration and the parameters characterizing the systematic component of the odometry error. It uses encoder readings as inputs and the readings from a laser range finder as observations. In this first filter, the non-systematic error is defined as constant and it is overestimated. Then, the estimation of the real non-systematic component is carried out through another Kalman filter, where the observations are obtained by two subsequent robot configurations provided by the previous augmented Kalman filter. There, the systematic parameters in the model are regularly updated with the values estimated by the first filter. The approach is theoretically developed for both the synchronous and the differential drive. A first validation is performed through very accurate simulations where both the drive systems are considered. Then, a series of experiments are carried out in an indoor environment by using a mobile platform with a differential drive.