Closing the Loop on Concentric Tube Robot Design: A Case Study on Micro-Laryngeal Surgery

• Published in: IEEE transactions on biomedical engineering Vol. PP; pp. 1 - 12
• Main Authors: Lin, Jui-Te, Girerd, Cedric, Ostrander, Benjamin T., Molaei, Parsa, Gilbert, Hunter B., Weissbrod, Philip A., Hwang, John T., Morimoto, Tania K.
• Format: Journal Article
• Language: English
• Published: IEEE 2024; Institute of Electrical and Electronics Engineers
• Subjects: Automatic; Concentric tube robots; Design optimization; Electron tubes; Engineering Sciences; Larynx; Medical robots and systems; Micro-laryngeal surgery; Multidisplinary design optimization; Optimization; Robots; Surgery; Surgical robotics; Uncertainty; Concentric tube robots; Micro-laryngeal surgery; Surgical robotics; Medical robots and systems; Multidisplinary design optimization
• ISSN: 0018-9294; 1558-2531; 1558-2531
• DOI: 10.1109/TBME.2024.3426489

Concentric tube robots (CTRs) are well-suited to address the unique challenges of minimally invasive surgical procedures due to their small size and ability to navigate highly constrained environments. However, uncertainties in the manufacturing process can lead to challenges in the transition from simulated designs to physical robots. In this work, we propose an end-to-end design workflow for CTRs that considers the oftenoverlooked impact of manufacturing uncertainty, focusing on two primary sources - tube curvature and diameter. This comprehensive approach incorporates a two-step design optimization and an uncertainty-based selection of manufacturing tolerances. Simulation results highlight the substantial influence of manufacturing uncertainties, particularly tube curvature, on the physical robot's performance. By integrating these uncertainties into the design process, we can effectively bridge the gap between simulation and real-world performance. Two hardware experiments validate the proposed CTR design workflow. The first experiment confirms that the performance of the physical robot lies within the simulated probability distribution from the optimization, while the second experiment demonstrates the feasibility of the overall system for use in micro-laryngeal surgical tasks. This work not only contributes to a more comprehensive understanding of CTR design by addressing manufacturing uncertainties, but also creates a new framework for robust design, as illustrated in the context of microlaryngeal surgery