  We present initial results in the development of a novel robot using RGBD
cameras, image segmentation, and a simple teat pose estimation algorithm for
automated milking. We relate on the analysis of the accuracy of different
commercial RGBD cameras in realistic conditions. Although preliminary, our
initial implementation shows that 2D image segmentation combined with point
cloud processing can achieve repeatable millimeter-scale precision in
estimating (synthetic) teat tip positions and cup attachment approach. The
solution is also applicable in a cloud robotics setup, with GPU-based
segmentation executed on an edge device or cloud.
