Abstract
<jats:p>Surgical robotics has evolved far beyond systems that simply mirror a surgeon's hand movements. Modern platforms can interpret tissue characteristics, regulate force in real time, and perform specific tasks with limited human input. This chapter traces that evolution from early mechanical systems of the 1980s to today's technologies enabling soft tissue manipulation, autonomous suturing, and intraoperative decision making. It explores key enablers of autonomy including computer vision, force sensing, machine learning, and safety architectures. The discussion distinguishes between clinically implemented autonomy and experimental developments while examining barriers to wider adoption. Critical issues such as regulatory approval, ethical concerns around consent and accountability, and the quality of training data are treated as core challenges. The chapter concludes by outlining future directions and their implications for surgical training, healthcare systems, and patient outcomes.</jats:p>