This paper proposes a robotic system to assist and collaborate with surgeons in Single Incision Laparoscopic Surgery (SILS) operations. The system, aim at solving the main drawbacks of this kind of surgery, is composed of a miniature camera robot and a redundant robotic grasper. Positioning of both robots inside the patient's abdomen is done by means of magnetic control. External magnetic sources are placed at the end effector of two robotic arms, and permanent magnets are integrated in the robots. Camera robot is provided with three permanent magnets, so both position and orientation can be controlled. Sliding control, which is robust against perturbations and parameter uncertainties, is chosen. Robotic grasper's redundancy makes possible autonomously obstacle avoidance and increases its workspace. The haptic device is designed so as surgeons can handle the grasper as if it were a conventional tool. In order to this aim, augmented reality is used to simulate a traditional tool in the visual feedback system, in substitution of the robotic grasper. Besides the telemanipulation, requirements for autonomously functions to assist surgeons in the specific tasks of suturing are discussed.

This paper focuses on autonomous movements to aid the surgeon to perform certain tasks. Robotic assistants have solved the drawbacks of Minimally Invasive Surgery (MIS) and provide additional skills to the surgeons. However, some authors argue that these systems could lengthen the operating time. The solution is the automation of certain maneuvers that help the surgeon during a surgical maneuver. This work proposes control architecture for a surgical robot capable of performing autonomous movements. In this way, a trajectory planner based on a behavior concept computes the required velocity vector of the surgical instrument hold by the robot. This planner has been implemented and tested on the control architecture of the surgical assistant CISOBOT, designed and developed at the University of Malaga.

This paper is focused on the motion control problem for a laparoscopic surgery robot assistant with an actuated wrist. These assistants may apply non-desired efforts to the patient abdomen. Therefore, this article proposes a control methodology based on three feedback levels, which have been defined as layers. These layers control different aspects of the endoscope movement. A low level assures the dynamic of the robot assistant is performed accordingly. The mid level emulates a passive wrist behavior to avoid any efforts over the abdomen. An external high level deals with the global movement planning. This architecture also makes easier to analyze the stability of the whole system. Finally, a real in-vitro experiment has been implemented with an industrial robot in order to contrast the validity of this article procedure.

This paper proposes a new user interface based on a maneuver recognition system, which models the surgeon behavior. This interface includes three different modules: data acquisition and coding, training system and on-line recognition system. The aim is defined as recognizing the surgeon movements while is performing a surgical maneuver, by using a 3D surgical tool tracker. The obtained measurements are converted in to movement symbols by means of a Wavelet transform and a fuzzy clustering. These symbols are used both for training HMM and for recognizing the current maneuver. The system has been tested in some in-vitro experiments performing a fictitious surgical protocol.

This paper proposes a Cartesian control scheme applied to a robotic assistant for laparoscopic surgery. This system's main characteristic is that it emulates the movements of a human assistant, guiding the laparoscopic camera with precision to focus on the area in question inside the patient. Furthermore this control scheme requires adjustment of certain parameters in order to prevent saturation of the manipulator's actuators, and therefore the robot has been studied in terms of manipulability. The proposed movement control scheme has been implanted in the ERM robot used to carry out trials on thirty two patients

This work presents an approach to the evaluation of two interfaces for the control of a robotic surgical assistant. Each interface is associated to a different mode of controlling the system: by the surgeon (voice commands) or by the assistant (tactile interface). This two modes are allowed by the design of the manipulator, developed to occupy a small volume in the operating room. To evaluate the interfaces, a rating scale for teleoperated systems is proposed.

This paper presents an adaptive trajectory planning method concerning to the robotic assistant ERM (endoscopic robotic manipulator), designed and developed by the authors for handling the camera in laparoscopic surgery. In order to emulate the human assistant, camera movements must be defined relative to the fulcrum point, where the optic passes through the patient skin and enters inside the abdominal cavity. Since the robot has a passive wrist, and it is not fixed to the operating table, the relative position between the robot camera holder and the insertion point is unknown. In this way, the proposed approach keeps the camera orientation according to the motion references in spite of this uncertainty, and compensates other unexpected disturbances about the relative robot-patient position. This motion planner is based on a schema of a cartesian motion controller with inner joint position-velocity loop, and has been tested by means of experimentation with alive animals.