Research trends on kinematics analysis of surgical robotics using machine learning techniques

Abstract

Due to the remarkable development of artificial intelligence technology, a lot of efforts are being actively made to utilize it in robotics field. Medical robots are being developed in various types such as serial robots, parallel robots, and continuous robots, taking into account the patient's anatomy and surgical method. For the precise control, researches are being conducted on accurate kinematic modeling and advanced control algorithms. However, there are limitations in applying traditional numerical approaches to some robots due to their high nonlinearity. Recently, learning-based techniques for kinematics analysis have been reported, demonstrating their potential as a promising solution to overcome nonlinearity. In this paper, we analyze the scope of application and research trends of artificial intelligence technology used in serial robots, parallel robots, and continuous robots, and discuss the possibility of learning-based control in medical robots and future research directions.