Dynamic robot manipulation using visual tracking

The authors consider the multiple applications of vision in the solution of dynamic robot and positioning problems such as catching, hitting, and intercepting a moving object. They propose a framework for qualitative reasoning about such problems, and then present a robust vision-based control strategy that uses a Kalman filter to track image features. In the formulation, a given positioning problem is transformed into one of constrained trajectory planning on a topological surface defined by the relationship between positions of the robot and observable image features. By considering only the qualitative properties of this surface, the need for precise calibration of the various components of the system is eliminated