Object Tracking and Interception System : Mobile Object Catching Robot using Static Stereo Vision

Abstract: The aim of this project is to examine the feasibility and reliability of the use of a low cost computer vision system to track and intercept a thrown object. A stereo vision system tracks the object using color recognition and then guides a mobile wheeled robot towards an interception point in order to capture it. Two different trajectory prediction models are compared. One model fits a second degree polynomial to the collected positional measurements of the object and the other uses the Forward Euler Method to construct the objects flight path. To accurately guide the robot, the angular position of the robot must also be measured. Two different methods of measuring the angular position are presented and their respective reliability are measured. A calibrated magnetometer is used as one method while pure computer vision is implemented as the alternative method. A functional object tracking and interception system that was able to intercept the thrown object was constructed using both the polynomial fitting trajectory prediction model as well as the one based on the Forward Euler Method. The magnetometer and pure computer vision are both viable methods of determining the angular position of the robot with an error of less than 1.5°.