Dimensionality Reduction in Controlling Articulated Snake Robot for Endoscopy Under Dynamic Active Constraints

Area of Science:

• Robotics
• Medical Technology
• Surgical Engineering

Background:

• Minimally invasive surgery (MIS) demands precise robotic control.
• Snake robots offer unique maneuverability for complex anatomical spaces.
• Existing control frameworks often lack real-time adaptation to dynamic constraints.

Purpose of the Study:

• To develop a real-time control framework for hyper-redundant snake robots in MIS.
• To ensure safe and precise robot navigation within anatomical constraints.
• To enhance surgeon control and reduce tissue interaction forces.

Main Methods:

• A proximity query (PQ) formulation was developed to monitor deviations from anatomical constraints.
• The PQ formulation was GPU-accelerated for high-frequency updates (>1 kHz).
• A novel polar coordinate motion parameterization enabled intuitive, low-DOF control.

Main Results:

• The framework achieved real-time control with smooth articulation and precise motion.
• Haptic guidance and resistance forces improved safety and user experience.
• Quantitative evaluations demonstrated practical value in simulated endoscopic tasks.

Conclusions:

• The proposed framework significantly enhances snake robot control for MIS.
• It offers improved safety, ergonomics, and precision in complex surgical environments.
• This technology has the potential to advance robotic-assisted minimally invasive procedures.