Vision Based Robotic Grasping Tracking of a Moving Object

Abstract:

Real-time vision allows the direct steering of a robotic manipulator. In this thesis we use a stereo rig mounted on an industrial robot (ABB IRB-6/2) which gives us information about the end effector position of a second robot (ABB IRB-2000/3). This second robotic manipulator performs the task of tracking a moving object, which in our case is a rolling ball.

The first concern of this project is to deal with the different kinds of problems occurring in such a system. After measuring the time-delays in our system we can establish the degree in which they effect it. We can then use these results for the actual control loop. More specifically a Kalman predictor scheme is implemented to produce estimates of coordinates for requested times, based on the time delay analysis. This Kalman predictor also helps us when we have lost track of either the robotic manipulator or the rolling ball.

Finally we perform the actual experiment of tracking the rolling ball. The experimental setup consists of the two robots and the stereo rig mentioned above, as well as a metallic ball rolling on a metallic board. The IRB-6 is mounted with the stereo rig and is set in a pre-decided position to be able to observe the movement of the rolling ball throughout the whole of its course. The other robotic manipulator performs the task of tracking the rolling ball, using as feedback the data received from the stereo rig.