Condition Monitoring for Image-Based Visual Servoing Using Kalman Filter
In image-based visual servoing (IBVS), the control law is based on the error between the current and desired features on the image plane. The visual servoing system is working well only when all the designed features are correctly extracted. To monitor the quality of feature extraction, in this paper, a condition monitoring scheme is developed. First, the failure scenarios of the visual servoing system caused by incorrect feature extraction are reviewed. Second, we propose a residual generator, which can be used to detect if a failure occurs, based on the Kalman filter. Finally, simulation results are given to verify the effectiveness of the proposed method.
KeywordsKalman Filter Feature Point Tracking Performance Visual Servoing Camera Frame
- 3.Malis, E., Chaumette, F., Boudet, S.: 2(1/2)d visual servoing. IEEE Trans. Robot. Autom. 15, 684–696 (1996)Google Scholar
- 11.Folio, D., Cadenat, V.: A sensor based controller able to treat total image loss and to guarantee non-collision during a vision-based navigation task. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 3052–3057 (2008)Google Scholar
- 15.Solanes, J.E., Armesto, L., Tornero, J., Girbes, V.: Improving image-based visual servoing with reference features filtering. In: IEEE International Conference on Robotics and Automation, pp. 3083–3088 (2013)Google Scholar