Researches On The Control System For A Parallel Tea-plucking Robot

The tea-plucking process is highly depending on the seasonality and the labor. There are mainly two ways to plucking tea. They are manual plucking and mechanized harvesting. The tea plucking manually is of good quality but without efficiency, leading to the tea plucking not in time, causing waste. As for mechanized harvesting is the opposite. It is high efficiency, but has difficulties to distinguish the flushes from old leaves. Due to bad tea quality, mechanized harvesting can’t meet the standards of high-quality green tea. So it can only be used for the bulk tea harvesting. Therefore, the development of high-quality green tea has been restricted and come to its bottleneck.In order to realize mechanical harvest for high-quality green tea, a prototype of parallel tea-plucking robot has been developed. A machine vision based system was constructed by our research team to detect the tea flushes, as well as a Delta parallel mechanism based robot. This paper mainly researches the control system of the parallel robot, in order to realize the rapidly and automatically plucking of the high-quality green tea according to the three dimensional coordinates of tea flushes detected by the machine vision system.According to the standards of high-quality green tea, the control system of parallel robot is researched. First, previous works of our research team are analyzed; including the tea flushes recognition system and the mechanism of the parallel robot. Then the overall plan of control system of the parallel robot is settled that the DSP controls the movement of the robot according to the three dimensional coordinates. The circuit of the controller based on DSP is also designed and made. The Vector module and the homogeneous coordinate transformation are used to derivate the inverse kinematics solution. Finally, programs are written, debugged to carry out the movement control experiment of the parallel robot according to the coordinates. Optimization suggestions are proposed after analyzing the results and problems of the experiment. Basic robot kinematics parameters such as velocity and accuracy are also evaluated according to the results.