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Robot hand tracking using adaptive fuzzy control

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5 Author(s)
Perez, C. ; Departamento de Ingenieria de Sistemas Industriales, Miguel Hernandez Univ., Spain ; Reinoso, O. ; Garcia, N. ; Neco, R.P.
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This paper presents a visual tracking system developed for a teleoperation project. The goal of this project is a both hands master-slave system in which the operator needs to see the robot hand (gripper) every time. For this reason, a new and robust algorithm to track the robot hand during its movement is developed. This is a model based tracking so the knowledge of the robot hand CAD model is needed (pose is obtained). This information is used to move a pan-tilt camera and keep the gripper centered in the image using an adaptive fuzzy logic controller. Due to the continuous gripper movement, we need a position predictor to reduce the error. In our case, the extended Kalman filter - EKF is used to do it. Vision based systems have a lot of empirically adjustable parameters for a good working. With the algorithm proposed in this paper, some parameters are auto-adjustable, so the system is easier to use and the robustness is increased.

Published in:

Fuzzy Systems, 2004. Proceedings. 2004 IEEE International Conference on  (Volume:3 )

Date of Conference:

25-29 July 2004