Position-based visual servoing via model-based design

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Date
2019-05
Authors
Choo, Jie Liang
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Abstract
Visual servoing is a technique where the motion of robot is controlled by the computer vision. There are two common visual servoing techniques that are currently been used in the world, which are Image-Based Visual Servoing (IBVS) and PositionBased Visual Servoing (PBVS). Various approaches such as Component-Based Design (CBD) and Model-Based Design (MBD) are used to design the mentioned visual servoing. Therefore, in this project, a combination of MBD with PBVS is proposed to design a follower robot, which is programmed to sense and track leader robot in 3D manner. In DoE, the follower robot is designed with an image sensor and ultrasonic sensor, allowing it to extract 3D data such as height, width of the pattern and the distance between leader and follower. A set of different scenarios are introduced to evaluate the performance of the follower robot, which is also categorized into straight line (Trajectory 1) and curved (Trajectory 2) trajectories. Experimental results show that the follower can track the leader easily for Trajectory 1- straight line, with high stability and short time, such as 1.40s for Experiment 1.1, 1.47s for Experiment 1.2 and 0.6s for Experiment 1.3. However, for Trajectory 2, the time required for overall tracking is slightly increased, such as C, thus lowering the efficiency of the tracking. In conclusion, the model-based design can achieve the minimal requirement of PBVS, which is to track the leader. The method however may be improved further in the future to minimise the overshoot and the optimise the tracking time.
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