Background Surgical robotics has enjoyed widespread clinical use over the last decade and brought a number of benefits and drawbacks. Surgeons benefit from improved dexterity and accuracy, as well as better visualization and a more intuitive interface, yet hospitals must contend with the cost and size of robotic systems [1]. Surgical robotics requires registering with moving anatomy, such as a scalpel incision or a suturing task. This can be accom plished with visual servoing [2] and machine learning [3], which would require keeping track of a straight line on human anatomy such as a hand, even if the anatomy is not stationary. A solution to this problem is collaborative control, where humans provide intuition while the robots provide the precision.