Vision System Based Position Tracking Control for an Integrated Electric Motor-Two-DoF Manipulator (ITM) Model

Penulis: Rina Ristiana,Midriem Mirdanies,Edwar Yazid,Rizqi Andry Ardiansyah,Yaya Sulaeman,Rahmat, .

Vision system based position tracking control of a two-DoF manipulator is a challenging work due to the uncertainties in the dynamics of electric motor, mechanical transmission, and environment. This paper proposes an integrated electric motor two-DoF manipulator (ITM) model with the camera system to be controlled by proposing the Extended Kalman Filter (EKF) method as a state estimator with a filter. Position tracking is performed to the azimuth and elevation angles of the manipulator where the target position is captured by the camera in pixels form, and transformed into 3D Cartesian coordinate. The angle values are obtained using inverse kinematics process with a geometrical approach, and taken as reference values for control system. To test the efficacy of the proposed plant model and the controller, two cases of position tracking are considered. First is carried out by estimating the motion of the manipulator with a moving target, and second is placing several static target points, and the end effector of manipulator moves to follow the target position. The results show that the position tracking control using the ITM model with EKF method produces reasonably accuracy and system stability under process and measurement noises in the form of Gaussian distribution.

IEEE IC2SE 2021

No. Arsip : LIPI-20220128
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