Continuum Reconfigurable Parallel Robots for Surgery: Shape Sensing and State Estimation with Uncertainty

Abstract

This letter examines shape sensing for a new class of surgical robot that consists of parallel flexible structures that can be reconfigured inside the human body. Known as continuum reconfigurable incisionless surgical parallel (CRISP) robots, these devices provide access to the human body through needle-sized entry points, yet can be configured into trusslike structures capable of dexterous movement and large force application. They can also be reconfigured as needed during a surgical procedure. Since CRISP robots are elastic, they will deform when subjected to external forces or other perturbations. In this letter, we explore how to combine sensor information with mechanics-based models for CRISP robots to estimate their shapes under applied loads. The end result is a shape sensing framework for CRISP robots that will enable future research on control under applied loads, autonomous motion, force sensing, and other robot behaviors.