  Active surgical robots lack acceptance in clinical practice, because they do
not offer the flexibility and usability required for a versatile usage: the
systems require a large installation space or a complicated registration step,
where the preoperative plan is aligned to the patient and transformed to the
base frame of the robot. In this paper, a navigation system for robotic
osteotomies is designed, which uses the raw depth images from a camera mounted
on the flange of a lightweight robot arm. Consequently, the system does not
require any rigid attachment of the robot or fiducials to the bone and the
time-consuming registration step is eliminated. Instead, only a coarse
initialization is required which improves the usability in surgery. The full
six dimensional pose of the iliac crest bone is estimated with a particle
filter at a maximum rate of 90 Hz. The presented method is robust against
changing lighting conditions, blood or tissue on the bone surface and partial
occlusions caused by the surgeons. Proof of the usability in a clinical
environment is successfully provided in a corpse study, where surgeons used an
augmented reality osteotomy template, which was aligned to bone via the
particle filters pose estimates for the resection of transplants from the iliac
crest.
