Dynamic error modeling and compensation in high speed delta robot pick-and-place process

In Delta Robot based high speed pick and place applications, the key for success is to sense, track and predict the workpiece position precisely in real time. However, because the workpiece is continuously moving on the conveyor, the vision and the robot may not share the same workspace, even the hand eye is precisely calibrated, it is difficult to achieve high precision in high speed system. Dynamics of all components have to be involved, modeled and compensated. In this paper, we first formulate the coordinate frame transformations between camera, conveyor and robot, then analyze the error propagation in the system work flow. By analyzing the sequences of the vision system, the camera trigger delay is modeled and compensated to synchronize the detected object position and the corresponding conveyor position. Instead of using the analytical model and calculate the robot motion time delay, we propose to model the robot motion delay as a fixed part plus a linear part and calibrate these parameters online automatically. A self feed high speed pick and place experimental platform is built and the proposed algorithm is implemented. The experimental results show the effectiveness.