Performance evaluation of vision-based control tasks

The tracking performance of vision-based control systems is evaluated and the optimal system configuration found. Configurations evaluated are serial or parallel image acquisition and processing, and pipeline processing. The basis of the optimization is the design of an optimal controller independent of the system configuration. Using this controller design a relation between system latency and maximum pixel error is derived. This relation is used to find maximum dynamic performance for the system configurations. The performance measure is the maximum velocity of the target in the image that can be tracked. The final comparison shows that processing in a pipeline obtains highest velocity due to high cycle rate of the system. The parameters for the point of maximum velocity are derived i.e., the optimal number of steps in a pipeline.