This paper deals with the position estimation problem by using the Kalman Filter with compensations for unexpected observations. In the position estimation problem, robot observations sometimes yield unexpected values, resulting in the deterioration of the estimation accuracy. For example, visual observation with an unmanned aerial vehicle often yields unexpected results because of blurred images. In this paper, we propose a method to assigns weights to the observations in order to remove the effects of unexpected observations. In the proposed method, unexpected observations are detected by comparing the observation values with its estimates; the weights of these observations are then determined. On the basis of simulation and experimental results, we demonstrate that a robot's position can be estimated by the proposed method.
|Title of host publication
|2015 IEEE Conference on Control and Applications, CCA 2015 - Proceedings
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - 2015 Nov 4
|IEEE Conference on Control and Applications, CCA 2015 - Sydney, Australia
Duration: 2015 Sept 21 → 2015 Sept 23
|IEEE Conference on Control and Applications, CCA 2015
|15/9/21 → 15/9/23
ASJC Scopus subject areas
- Control and Systems Engineering