Jaydev P. Desai

In Brief Objective: To review the history, development, and current applications of robotics in surgery. Background: Surgical robotics is a new technology that holds significant promise. Robotic surgery is often heralded as the new revolution, and it is one of the most talked about subjects in surgery today. Up to this point in time, however, the drive to develop and obtain robotic devices has been largely driven by the market. There is no doubt that they will become an important tool in the surgical armamentarium, but the extent of their use is still evolving. Methods: A review of the literature was undertaken using Medline. Articles describing the history and development of surgical robots were identified as were articles reporting data on applications. Results: Several centers are currently using surgical robots and publishing data. Most of these early studies report that robotic surgery is feasible. There is, however, a paucity of data regarding costs and benefits of robotics versus conventional techniques. Conclusions: Robotic surgery is still in its infancy and its niche has not yet been well defined. Its current practical uses are mostly confined to smaller surgical procedures. Robotic surgery is a proliferating new technology despite a paucity of information comparing it with conventional laparoscopy. This article reviews the early data and attempts to give the reader a broad perspective on robotic surgery.

This paper addresses the control of a team of nonholonomic mobile robots navigating in a terrain with obstacles while maintaining a desired formation and changing formations when required, using graph theory. We model the team as a triple, (g, r, H), consisting of a group element g that describes the gross position of the lead robot, a set of shape variables r that describe the relative positions of robots, and a control graph H that describes the behaviors of the robots in the formation. Our framework enables the representation and enumeration of possible control graphs and the coordination of transitions between any two formations.

We investigate feedback laws used to control multiple robots moving together in a formation. We propose a method for controlling formations that uses only local sensor-based information, in a leader-follower motion. We use methods of feedback linearization to exponentially stabilize the relative distance and orientation of the follower, and show that the zero dynamics of the system are also (asymptotically) stable. We demonstrate in simulation the use of these algorithms to control six robots moving around an obstacle. These types of control laws can be used to control arbitrarily large numbers of robots moving in very general types of formations.

Robotic artificial muscles are a subset of artificial muscles that are capable of producing biologically inspired motions useful for robot systems, i.e., large power-to-weight ratios, inherent compliance, and large range of motions. These actuators, ranging from shape memory alloys to dielectric elastomers, are increasingly popular for biomimetic robots as they may operate without using complex linkage designs or other cumbersome mechanisms. Recent achievements in fabrication, modeling, and control methods have significantly contributed to their potential utilization in a wide range of applications. However, no survey paper has gone into depth regarding considerations pertaining to their selection, design, and usage in generating biomimetic motions. In this paper, we discuss important characteristics and considerations in the selection, design, and implementation of various prominent and unique robotic artificial muscles for biomimetic robots, and provide perspectives on next-generation muscle-powered robots.

In Brief Objective: To evaluate the role of force feedback with applications to minimally invasive surgery (MIS). Two research hypotheses were tested using our automated laparoscopic grasper. Summary Background Data: Conventional laparoscopic tools do not have the ability of providing force feedback to a surgeon when in use with or without robotic surgical systems. Loss of haptic (force and tactile) feedback in MIS procedures is a disadvantage to surgeons since they are conventionally used to palpating tissues to diagnose tissues as normal or abnormal. Therefore, the need exists to incorporate force feedback into laparoscopic tools. Methods: We have developed an automated laparoscopic grasper with force feedback capability to help surgeons differentiate tissue stiffness through a haptic interface device. We tested our system with 20 human subjects (10 surgeons and 10 nonsurgeons) using our grasper to evaluate the role of force feedback to characterize tissues and answer 2 research hypotheses. Results: Our experiments confirmed 1 of our 2 research hypotheses, namely, providing both vision and force feedback leads to better tissue characterization than only vision feedback or only force feedback. Conclusions: We have validated 1 of our 2 research hypotheses regarding incorporating force feedback with vision feedback to characterize tissues of varying stiffness. This paper focuses on evaluating the role of force feedback in minimally invasive surgery using an automated laparoscopic grasper developed in our laboratory. Several experiments with human subjects were performed to characterize various tissue samples using only vision feedback, only force feedback, both vision and force feedback, and direct exploration.