Continuum manipulators are robotic systems composed of continuously bending structures, enabling smooth and flexible motion similar to biological trunks or tentacles. Unlike conventional rigid-link robots, continuum robots can navigate through highly curved and confined environments that are difficult or impossible for traditional robots to access.
This enhanced accessibility makes continuum robots highly attractive for a wide range of applications. In industrial settings, they can operate inside complex environments such as aircraft turbines, pipelines, semiconductor manufacturing equipment, and building infrastructures where narrow and tortuous paths are common. Their ability to maneuver within constrained spaces enables inspection, maintenance, and precision manipulation tasks that are otherwise difficult with rigid robotic systems.
Continuum robots are also particularly promising in medical applications. By entering the human body through natural orifices such as the mouth, vagina, or anus, these robots can navigate through curved anatomical structures to reach target lesions within organs such as the stomach or colon. This approach enables minimally invasive or even incisionless procedures, offering significant clinical benefits such as reduced trauma, faster recovery, and lower risk of complications.
Despite these advantages, continuum robotic systems present several fundamental technical challenges. Their flexible structures and cable-driven actuation introduce complex nonlinear behaviors, including tendon friction, hysteresis, cable elongation, and structural compliance. These effects make precise modeling, control, and positioning significantly more difficult than in conventional rigid robots.
Research in SurGLab focuses on addressing these challenges to enable reliable, dexterous, and intelligent continuum robotic systems capable of operating in complex environments.
Miniaturized actuation systems, cable-driven mechanisms, and dexterous joint structures for highly flexible manipulators.
Dynamic modeling of tendon–sheath mechanisms, friction and hysteresis modeling, and compensation strategies for accurate motion control.
Intuitive master–slave control, motion scaling, and operator interfaces for precise manipulation in confined environments.
Shared control, learning-based motion generation, and AI-assisted task automation for complex operations.