Design, implementation, and validation of a control framework for haptics-enabled multi-arm robot-assisted laparoscopic surgery

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Robot-assisted surgery, especially robot-assisted laparoscopy (RL), has gained momentum in Canada, the US, and Europe in the past five years. RL systems have simplified the workflow of laparoscopic minimally invasive surgeries, decreased time of surgery, enhanced surgeons' precision and dexterity, and made remote surgery possible. RL systems use multiple robots around the operating table while their tip instruments (graspers, scissors, needle holders, and laparoscope cameras) are inserted into the patient's abdomen through 8 to 12mm incisions. During RL surgery, a controller continuously relays motion commands from a remote-control console (surgeon's console) to the surgical robots. At the same time, the laparoscope camera sends video from inside the patient's abdomen to the surgeon's console. Since the surgeon merely has visuals from inside the abdomen and the console is away from the operating table, the surgeon is not necessarily aware of the robots' shapes outside the patient's body. Thus, there is a significant risk of collision between the robots that may result in irrecoverable injury to the patient or serious damage to the expensive robots. To alleviate the risk of collision between surgical robots, the investigators of this research and Kinova (industrial partner) have joined forces to develop and test a novel, fast, and autonomous collision avoidance technology for RL surgeries. The investigators have formed a scientific network with biomedical, robotics, surgery, and software expertise to eliminate this safety concern in the partner's surgical robots. As an additional safety feature, they are developing a robust haptic feedback technology to relay vibrational alerts about imminent collisions to the surgeon's hands during the surgery. Kinova is a leading manufacturer of surgical robots in North America and will be the first in the world to provide off-the-shelf surgical robots with autonomous collision avoidance features. With the partner's planned knowledge translation activities, this technology will result in safer surgical robots that need short integration time for RL surgeries and ultimately facilitate broader democratization of robotic surgery for Canadian people.