Towards Tracking a Semi-autonomous, Pneumatic Colonoscope Robot

We describe a semi-autonomous tracking technique based on a Bayesian prediction mechanism for a pneumatic colonoscopy robot. One of the principal problems in using a robot colonoscope is to determine its position or displacement after it has been inserted into the colon. To address this problem for our robot, we have developed a temporal Bayesian framework that uses the observations of the air flow rate and pressure in the tube guiding the robot to predict the current location of the robot. Our experimental results show that the predicted location and velocity of the robot are accurate over most of the time-steps, with a maximum error of 11.5 cm (about 2.5 times the length of the robot's head) occurring only 7% of the time.