MOTIVATION: Many proteins are partially disordered in physiological conditions and only fold, fully or partially, upon binding. Their structural analysis is challenging because the accessible information, typically chemical shifts (CS) from nuclear magnetic resonance experiments, are averages over broad ensembles of conformations. We aim to develop a database for the analysis of such data in terms of conformational distributions of the protein backbone rather than of individual high-resolution structures. RESULTS: Glutton is the largest available database linking CS and protein 3D structures (5270 entries organized in three levels) and is searchable via a python script. It generates statistical distributions of ϕ-ψ dihedral angles based on CS or vice versa. Such ϕ-ψ distributions are used to calculate structural ensembles of partially disordered proteins from their CS. For folded proteins, such ensembles are excellent starting points for further refinement with additional experimental restraints (structure determination) or computational methods (structure prediction). AVAILABILITY AND IMPLEMENTATION: Glutton is freely available at https://github.com/YeeHo/Glutton. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

This paper describes the mechanical design and a cognition system for a novel concept-of-camera robotic assistant. The system combines the advantages of intra-abdominal devices and autonomous camera navigation. The robotic assistant is composed of a magnetic intra-abdominal camera robot with two internal cable-driven degrees of freedom and an external robot that handles an external magnet. The intelligence of the robot is implemented in a cognitive architecture based on a long-term memory that stores the robot's knowledge and learning capabilities to improve the robot's behavior. The navigation strategy combines a reactive control based on instrument tracking and a proactive control based on predefined behaviors, depending on the actual state of the task. The robot's learning capabilities include a semantic customization, to adapt the camera's behavior to the surgeon's preferences, and reinforcement learning, to improve the camera navigation strategy. This paper details both the hardware implementation of the system and the software implementation in a robotic operating system architecture. The cognition system and the performance of the cable-driven mechanism have been validated with a set of in vitro experiments. Moreover, the camera robot has been evaluated through an in-vivo experiment in a pig.

This paper introduces a new Learning from Demonstration (LfD)-based method that makes usage of robot effector forces and torques recorded during expert demonstrations, to generate force-based haptic guidance reference trajectories on-line, that are intended to be used during haptic shared control for additional operator `guidance'. Derived haptic guidance trajectories are superimposed to master-device inputs and feedback forces within a bilateral control experiment, to assist an operator by the guidance during peg-in-hole insertion. We show that 96 peg-in-hole expert demonstrations were sufficient to obtain a good model of the task, which was used on-line to generate haptic guidance trajectories in real-time with a 1kHz sampling rate.

This paper describes the design and implementation of a robotic vision system for single-site surgery. The system is composed of a wireless miniature camera robot with magnetic pan and tilt capabilities, and an external robotic arm to guide the camera along the abdominal wall. The camera robot is provided with a set of magnets, and a magnetic holder is attached at the end effector of the manipulator. This way, the camera robot can be displaced to obtain additional viewpoints of the abdominal cavity by displacing the external manipulator. The first prototype of the camera robot with an embedded LED lighting system is described. To properly displace the robotic arm over the abdominal wall, a hybrid force-position control has been developed, which includes a torque compensation module in order to obtain an appropriate orientation of the end effector. The contact surface has been assumed to be an elastic model, which stiffness matrix is estimated with a recurrent least squares algorithm. Finally, an in-vitro experiment to validate the control scheme proposed is presented.

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.

The main objective of this paper is to minimize the occluded areas in order to recognize the navigation of the surgeon's tools for a two-arm autonomous robotic system for laparoscopic procedures. This robotic assistant needs the tracking of the surgeon's surgical gestures in order to recognize the current maneuver and to execute the automated tasks of the robot. The surgical tools pose estimation is carried out by a Multiple Extended Kalman Filter (MEKF), where the movement models of the surgical tools depend on the maneuver which is being developed. This information is obtained by a maneuvers recognition system which is a part of the multimodal human machine interface (HMI) of the robot. The method proposed for reducing shadows has been applied to three in-vitro maneuvers which appear in the majority of the surgical protocols. The experiments show the behavior of this method for different time intervals of the occlusions.

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.

Presents a robotic assistant for helping surgeons in minimally invasive surgery. This prototype does not require any modification of a standard operation theatre (furniture or surgery tools) for its installation and its putting into operation. Due to its modular design, the robotic assistant is defined as a multi-purpose tool that has been successfully used in laparoscopic surgery, cystoscopy diagnostic and transurethral resection. The system has been tested by using both patient simulators and animals for experimentation purposes.

This paper presents a speed planning and generation algorithm for mobile robots that work under some kind of speed limitations. The proposed method takes the information about these speed constraints and the moving obstacles in the environment, and provides a safe speed profile which allows to build a trajectory that bypasses such obstacles. The method has been successfully tested in the RAM-2 mobile robot.

The paper deals with speed control for autonomous mobile robots. First a trajectory planner attaches a speed component to the postures of a path by considering speed limitations introduced by the vehicle and by task specifications. In order to provide robustness during task execution in the real world, environment feedback is used to dynamically adjust the speed of the vehicle to the presence of unexpected obstacles, both static and mobile. This is accomplished by combining the planned speed profile with the outputs of two reactive controllers. The system has been successfully implemented within the control architecture of the RAM-2 mobile robot.

This paper presents methods for planning mobile robot trajectories by considering the kinematic and dynamic constraints on the vehicle motion. The resulting path is smooth and quasilinear in curvature variations. The maximum value of the curvature can be assured to be smaller than the value given by the constraints. Furthermore, speeds along the path are planned subject to the kinematic and dynamic constraints. The resulting trajectories provide ideal conditions for high precision path tracking and positioning. In the paper we present the application of the proposed methods to RAM-1, a new mobile robot designed and built for indoor and outdoor industrial environment.>