  The endoscopic camera of a surgical robot provides surgeons with a magnified
3D view of the surgical field, but repositioning it increases mental workload
and operation time. Poor camera placement contributes to safety-critical events
when surgical tools move out of the view of the camera. This paper presents a
proof of concept of an autonomous camera system for the Raven II surgical robot
that aims to reduce surgeon workload and improve safety by providing an optimal
view of the workspace showing all objects of interest. This system uses
transfer learning to localize and classify objects of interest within the view
of a stereoscopic camera. The positions and centroid of the objects are
estimated and a set of control rules determines the movement of the camera
towards a more desired view. Our perception module had an accuracy of 61.21%
overall for identifying objects of interest and was able to localize both
graspers and multiple blocks in the environment. Comparison of the commands
proposed by our system with the desired commands from a survey of 13
participants indicates that the autonomous camera system proposes appropriate
movements for the tilt and pan of the camera.
