Automated Motion System of 5-DOF Hybrid Serial-Parallel Manipulator for Invasive Medical Procedures

Abstract

In the medical profession where accuracy is vitally critical, operations are increasingly adopting robotic technology to eliminate mistakes and improve precision. Current robotic-assisted surgical systems are sometimes limited in their usefulness in complex procedures because they lack real-time haptic feedback and adaptive motion control, despite improvements in the field. A 5-DOF hybrid serial-parallel manipulator is presented in this study, which has been developed to enhance dexterity, motion stability, and real-time force feedback in a range of minimally surgery applications. During surgical procedures, the device enhances precision and control by combining AI-assisted motion correction with a haptic glove-controlled master-slave mechanism. Increased trajectory stability, reduced force application errors, and greater surgical precision are all demonstrated by simulations and experimental validation in MATLAB Simulink. The findings indicate that adaptive AI and enhanced haptic feedback can significantly improve robotic-assisted procedures, making them more effective and reliable for a range of minimally invasive surgeries. In the future, the focus will be on improving response time, making the system more adaptive, and integrating it into the actual environment.