Ranking Inverse Kinematic Solutions for the Control of a CT-compatible Robotic Platform

Robotic systems have been widely employed for many needle biopsy applications, such as transthoracic lung biopsies that enable early diagnosis of primary lung cancers with small, distal lesions. The CRANE robot, a robotic needle positioning system for CT guided procedures, is one such system that has demonstrated a low-profile, high dexterity, and a large number of degrees of freedom. In this thesis, we present an end-to-end automated control scheme for the CRANE robotic platform that optimizes a robotic configuration over several defined metrics relevant to the successful completion of a transthoracic needle biopsy procedure. For a given needle tip target pose, multiple viable arm configurations are generated and ranked based several metric criteria. Once a configuration is chosen, a planner is run to find a collision-free path from the robot’s initial position outside of the CT-bore to this final configuration within the bore.