Abstract

In teleoperated Robot-Assisted Minimally-Invasive Surgery (RAMIS), a surgeon controls the movements of instruments inside the patient’s body via a pair of robotic joysticks. RAMIS has transformed many surgical disciplines, but its full potential is still to be realized. In this chapter we propose a pathway towards overcoming several bottlenecks that are related to transparency and stability of the teleoperation channels that mediate RAMIS. We describe the traditional system centered and the more recent human-centred approaches to teleoperation, and the special considerations for RAMIS as an application of teleoperation. However, the human-centered approach is still one sided view focusing on the surgeon but neglecting the learning capabilities of robotic systems. Hence, we consider a more general idea of physical human-robot orchestration with coevolution of mutual internal representations – of the human and the robot, and discuss it in comparison to human-human collaboration over teleoperated channels.

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