  Camera parameters not only play an important role in determining the visual
quality of perceived images, but also affect the performance of vision
algorithms, for a vision-guided robot. By quantitatively evaluating four object
detection algorithms, with respect to varying ambient illumination, shutter
speed and voltage gain, it is observed that the performance of the algorithms
is highly dependent on these variables. From this observation, a novel active
control of camera parameters method is proposed, to make robot vision more
robust under different light conditions. Experimental results demonstrate the
effectiveness of our proposed approach, which improves the performance of
object detection algorithms, compared with the conventional auto-exposure
algorithm.
