A Platform for Developing Robotic Navigation Strategies in a Deformable, Dynamic Environment

Abstract

While in vivo robotic locomotion has demonstrated its potential through a number of means, sensing and closed-loop control for such devices have not been at the forefront of research. By enabling real-time navigation, capsule endoscopy could transform from passive capsule endoscopes (CEs) and remote-controlled robotic CE devices into semi- or fully autonomous, surgical tools. In this work, a novel robotic endoscope platform (REP) is designed and tested. This platform will be used to evaluate control, localization, and mapping techniques necessary to endow a robotic CE with autonomous features. REP performance was benchmarked against design requirements that included sensing, speed, and maneuverability. It was found that the REP could accelerate to a maximum speed of 80 mm/s in less than 0.2 s and could achieve a zero-point turning radius. Most significantly, a low-cost image segmentation algorithm was developed to enable real-time lumen navigation/center tracking. Visual navigation time trials were compared to manual user trials through a 90-degree turn in a deformable simulator, exhibiting mean run times 34% faster than manual users. This demonstrates the REP's maneuverability and sensing capabilities allowing for future implementation of a range of advanced sensing and control techniques ahead of robotic CE adoption.