At its core, surgical robotics augments surgical care through a fusion of human and machine capabilities to deliver care where and when the patient requiresit. Like many endeavors of this type, National Aeronautics and Space Administration (NASA) and US Militaryprovided the brunt of the initial investment. In the 1980s, NASA Ames Research Center explored the concept of transporting one’s “aware­ness” to another environment through what is now known as “virtual reality” or “telepresence,” with the intention of reviewing imaging data from the Voyager space probe missionswhile in the NASA labs [1]. Dr. Joseph Rosen, a hand surgeon at Stanford, saw the head-mounted displays and early hand controlleras a way to per­form complex open microsurgery remotely. This prompted the enlistment of Stanford Research Institute’s (SRI) Phil Green, PhD, to bring their robotics exper­tise to the venture and establish the Green Telepresence System in 1987. Dr. Rosen took a job with Dartmouth, passing the clinical responsibility of the project to US Army Colonel Dr. Richard Satva in 1988, who joined the team at SRI to develop the rst “Telepresence Surgery System” consisting of a telepresence surgeon’s worksta­tion (Fig1.1) and remote surgical unit (Fig1.2).

At SAGES in 1989, Dr. Jacques Perissat debuted a video of laparoscopic chole­cystectomy to much controversy. Despite this controversy,Dr. Satava recognized

In 1992, a video of the Greene Telepresence system pealing a grape was shown to the Army Surgeon General. Dr. Satava was then assigned to the Advanced Research Projects Agency (ARPA, which subsequently became DARPA), where he would oversee the development of telepresence systems. The military’s goal was to develop a mobile surgical unit that could be installed in an armored vehicle and controlled by a surgeon remotely from a mobile army hospital (MASH),allow­ingthen the delivery ofimmediate surgical care to soldiers in transit from the battle­eld. The system was named Medical Forward Advanced Surgical Treatment (MEDFAST), drawing on inspiration from Robert Heinlein’s description of medical systems illustrated in his science ction novel Starship Troopers (Fig1.3). The sys- tem successfully repaired swine stomach, intestine, and vascular injuries (Fig1.4), [2, 3]. While the robotically assisted procedures took longer than traditional open procedures, it was noted the procedures could be completed more quickly

Dr. Yulun Wang founded Computer Motion in 1990 to develop a robotic endoscope holder, initially with funding from NASA.This also attracted funding from ARPA that led to the development of Automated Endoscopic System for Optimal Positioning (AESOP). This system was a voice-controlled endoscope that became the rst FDA-approved surgical robot [7]. This system then incorporated bed­mounted robotic arms to become the Zeus surgical system with the intended use in remote telesurgery procedures. The system was used by Dr. Jacques Marescaux to complete a transatlantic surgery (“The Lindbergh” surgery) between NewYork City and Strausburg France in 2001, removing a woman’s gallbladder. This may have been the most expensive surgical procedure to date, with telecommunications costs alone costing over US$1 million [8]. Additionally, the Zeus was the platform that helped facilitate the rst national telesurgery program in Ontario, Canada. This group, led by Dr. Mehan Anvari at McMaster University, completed collaborative fundoplications, hemicolectomies, and other general surgery procedures working with less experienced surgeons over 400km away [9–11].

The initial target market for the use of the Da Vinci system was actually in car­diac surgery with plans to incorporate technology to compensate for theheart’s motion [14, 15]. While the technology was impressive, there was limited enthusi­asm within the cardiac surgery community. A new market was discovered in the urologic community. Dr. Clement-Claude Abbou of Paris had been a pioneer in laparoscopic prostatectomy, working with colleagues in Germany, Dr. Binder and Dr. Kramer. The oncologic equivalence of the minimally invasive approach, com­pared to open, was demonstratedin clinical trials; however, the procedure had a tremendous learning curve that limited the laparoscopic approach to specialized centers [16]. Dr. Abbou was the rst to perform a minimally invasive prostatectomy using a Da Vinci robot on loan from the cardiac surgery department, and his tech­nique was quickly replicated by the Germans [17]. These ndings were discussed with Dr. Menon of Detroit, who had been attempting to establish a minimally inva­sive surgery prostatectomy program but was limited by the technical challenges and poor outcomes [18]. Dr. Menon found the robotic platform attened his learning to perform minimally invasive surgery. He was able to quickly establish equivalent oncologic and superior functional outcomes as compared to open surgery. He then went on to establish a program at Henry Ford Hospital to popularize the approach [19]. Prior to the introduction of the robotic platform in the United States, few mini­mally invasive prostatectomies had been performed. As of 2003, 12% of prostatec­tomies were performed using the robot and as of 2021 around 90% of prostate surgery utilized the robot [20, 21]. There has been rapid uptake in gynecologic, thoracic, and general surgery elds and adoption of robotic platforms rapidly increasing the number and types of procedures performed in a minimally inva­siveinvasive fashion. This trend was possible due to the improved ergonomics, range of motion, and visualizationof the robotic platforms.

With innovation, there will always be controversy. In the early days of laparo­scopic surgery, opponents pointed to higher costs, high conversion rates, and worse outcomes in certain circumstances [22, 23]. As was argued by proponents of laparo­scopic surgery, then, these were all artifacts of both the surgeon and healthcare system learning curve. Minimally invasive approaches to a many surgical proce­dures have demonstrated equivalent oncologic and functional outcomes with less pain, shorter hospital stays, and fewer postoperative complications [24]. Robotic

In the mid-2000s, computer chips called Graphics Processing Units (GPUs), ini­tially meant for producing high-end graphics for video games, began being used for more general-purpose computing. They were found to be very effective at perform­ing tasks known as machine learning or deep learning. Previously, this type of work had to be done with large mainframe computers, but with GPUs the work could be done with a desktop computer. This general innovation and massive reduction in