Redundancy optimization strategy for hands-on robotic surgery.

Area of Science:

• Robotics in Medicine
• Surgical Technology
• Human-Robot Interaction

Background:

• Operating Room (OR) encumbrance from large medical equipment, such as surgical microscopes, poses challenges for hands-on cooperative surgery.
• Redundant robots can help mitigate these spatial constraints.
• Effective control strategies are needed to optimize robot movement within limited OR space.

Purpose of the Study:

• To introduce and evaluate a novel Null Space Optimization (NSO) strategy for controlling the manipulator's elbow position.
• To ensure robot movement adheres to procedural spatial requirements and physical joint limits.
• To compare the performance of the new NSO strategy against existing methods.

Main Methods:

• Development of a new Null Space Optimization (NSO) strategy.
• Application of the NSO strategy to a 7 degrees of freedom (dof) lightweight robot (LWR4+).
• Comparative analysis against damped posture and fixed optimal posture strategies with non-expert users under varying encumbrance limitations (20deg and 100deg).

Main Results:

• The NSO strategy demonstrated versatility in maintaining elbow mobility.
• It ensured safe distances from null space boundaries, contributing to smooth guidance trajectories.
• Performance was evaluated across different encumbrance levels and compared to established methods.

Conclusions:

• The proposed NSO strategy is effective in managing surgical robot arm configurations within confined operating spaces.
• It offers a promising approach for enhancing safety and maneuverability during cooperative robotic surgery.
• Further research is needed to assess its feasibility in actual surgical settings.