  We present a robust markerless image based visual servoing method that
enables precision robot control without hand-eye and camera calibrations in 1,
3, and 5 degrees-of-freedom. The system uses two cameras for observing the
workspace and a combination of classical image processing algorithms and deep
learning based methods to detect features on camera images. The only
restriction on the placement of the two cameras is that relevant image features
must be visible in both views. The system enables precise robot-tool to
workspace interactions even when the physical setup is disturbed, for example
if cameras are moved or the workspace shifts during manipulation. The
usefulness of the visual servoing method is demonstrated and evaluated in two
applications: in the calibration of a micro-robotic system that dissects
mosquitoes for the automated production of a malaria vaccine, and a macro-scale
manipulation system for fastening screws using a UR10 robot. Evaluation results
indicate that our image based visual servoing method achieves human-like
manipulation accuracy in challenging setups even without camera calibration.
