One of the major functions brought by robots in Minimally Invasive Surgery is endoscope holding. This consists, for the user, in placing the camera at a desired location which the robot will maintain still once he/she releases it. This behavior is usually achieved with rigid position servoing, leading to possibly high forces generated and safety issues. Model-based weight compensation is an alternative solution. However, endoscopic cameras' weight is difficult to model as their gravity parameters can change during the same surgery. In this paper, an algorithm is presented as an option to cope with this variability in the gravity model without using rigid position servoing. The surgeon first positions the camera in a comanipulation mode (gravity compensation). When he/she releases the camera, if the gravity model is not accurate, the endoscope presents a drift. In this case, a controller brings the endoscope back to its release position by combining low gain position control and model adaptation. Once stabilized, the system is switched back to a zero-stiffness mode. Two in-vitro experiments were performed in which a user manipulates an endoscope whose configuration of mass is changed. In one case, the mass in the gravity model was set to half of the actual one. In the second case, a variable weight was attached to the endoscope. The algorithm successfully updated the model for each experiment reducing position errors by 95% and 57%, respectively.

Classic Minimally Invasive Surgery (MIS) is an ergonomic burden for assistants and surgeons. The former need to adopt uncomfortable positions for hours while holding a camera to track the latter’s gestures inside the patient. This incurs assistant’s muscle fatigue which can lead to tremor or drift of the video feedback. A backdrivable robotic holder can be attached to this device in order to compensate its weight. This allows the user to place the camera at a desired position which the robot will steadily keep once he/she releases it. However, endoscopic cameras present difficult-to-model accessories whose gravity parameters can change during the same surgery. If these changes are not foreseen by the gravity model of the robot this results in a fall of the endoscope each time it is released. Therefore, it is desired to firstly detect if there is a fall in order to be able to correct it. In this article a fall detection method for a comanipulated robotic endoscope holder is proposed. It evaluates smoothness of the robot end effector trajectory to identify whether the user manipulates the instrument or it has been released and poorly compensated. An experiment was carried out with 10 subjects where 240 releases of the endoscope were performed while it was poorly compensated. The algorithm succeeded to detect the falls with sensitivity up to 99.17%.

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