Intelligent Control for Human-Robot Cooperation in Orthopedics Surgery

Area of Science:

• Robotics
• Orthopedic Surgery
• Human-Robot Interaction

Background:

• Widespread adoption of robots in orthopedic clinics is hindered by challenges in surgeon-robot cooperation.
• Existing human-robot cooperation methods and control strategies require improvement for intuitive interaction.

Purpose of the Study:

• To review human-robot cooperation methods in robot-assisted orthopedic surgery.
• To propose an intelligent admittance control method for intuitive human-robot interaction.
• To enhance safety and precision in robot-assisted orthopedic procedures.

Main Methods:

• A literature review of human-robot cooperation and control strategies.
• Development of an intelligent admittance control combining fuzzy model reference learning control (FMRLC) and virtual constraint (VC) control.
• Implementation of a variable damping parameter model using FMRLC for surgeon motion tracking with minimum jerk trajectory.
• Integration of VC control based on virtual fixtures for defining safe surgical areas.

Main Results:

• The proposed intelligent control method demonstrated improved intuitive interaction and high precision in experiments on an acrylic model.
• A pilot study on a sawbone model for bone tumor resection confirmed the method's effectiveness.
• The 6-DOF articulated robot test platform facilitated the validation of the control strategy.

Conclusions:

• The intelligent admittance control method effectively addresses the need for intuitive human-robot interaction in orthopedic surgery.
• The developed system enhances both the precision and safety of robot-assisted surgical procedures.
• This approach shows significant potential for increasing the utilization of robotic systems in orthopedic clinics.