This paper introduces a robotic rehabilitation system for upper limb therapy, utilizing a manipulator controlled through variable admittance control. The proposed approach allows dynamic modulation of the patient's mobility within a predefined spatial tolerance region, which is set by the therapist at the beginning of each session based on the patient's capabilities. The system adjusts movement constraints based on the applied force, promoting guidance along the intended path. Specifically, it supports motion along the path tangent while increasing resistance to deviations, but only when the applied force pushes the patient away from the trajectory. Conversely, when the movement is directed toward realignment, the system permits greater freedom in all directions that facilitate a return to the predefined path. To validate the proposed approach, an experimental study was conducted to analyze the system's behavior in practice. The results demonstrate the system's effectiveness in modulating movement assistance and resistance based on patient interaction, ensuring both guidance and adaptability within the rehabilitation process.

An accurate orientation estimation is a primary requirement in autonomous navigation tasks of mobile robots, especially when such operation is involved in the solution of the position estimation problem (e.g. dead reckoning navigation systems). This is the case of Autonomous Underwater Vehicles (AUVs), subject of this paper; for this class of robots, a complete attitude estimation system based on the adaptation of a Nonlinear Complementary Filter (NCF) is proposed. The presented filter fuses the measurements of an Inertial Measurement Unit (IMU) comprising magnetometers. The integration of a single-axis Fibre Optic Gyroscope (FOG) is evaluated to overcome issues due to magnetic disturbances. In addition, a calibration procedure for magnetometers to be exploited within the attitude estimation filter is proposed. The whole system has been experimentally validated and tested on the University of Florence Typhoon AUV; the results prove that the proposed approach allows to obtain a reliable orientation estimate even in the presence of external unpredictable disturbances.

Object of the present work is the development of a control system able to increase performances of the industrial laser marking process. The laser marking is performed by a system called “galvanometer scanning head”, that is composed of special actuators known as “galvanometers”, which are used to control the positions of mirrors able to properly guide a laser beam in order to engrave a desired shape on an object placed on the working table. In particular authors have developed a simplified model of system including drive and sensor stages. This model has been further verified and calibrated with experimental tests. An innovative control strategy able to significantly improve the response of the system respect to a previously developed controller has been proposed. Both controllers have been tested and compared experimentally showing a significant of improvement of the innovative controller respect to the conventional one.

In this paper, the development and the experimental testing phases of an innovative assistive device for hand disabilities are presented. This robotic device is based on an parallel kinematic chain applied to a single phalanx architecture and it is designed to be extremely portable to easily assist people with physical disabilities in their everyday lives. Focusing on patients with hand opening disabilities, the authors have developed a model-based methodology which starting from the motion capture of the patient fingertip trajectories is able to define the mechanism that better fits with such trajectories. The authors have validated the proposed innovative mechanism by developing a portable Hand Exoskeleton System (HES) prototype and performing a suitable preliminary testing campaign. The testing phase of the real prototype on a group of patients is currently ongoing.

Weighing-in-motion (WIM) systems automatically perform the dynamic weighing of railway vehicles while the trains are running on the lines through a reasonable number of measurement points placed along the track. Such intelligent systems may overcome disadvantages in terms of costs and traffic management, which are typical of conventional static weighing systems. In this paper, we present an innovative algorithm for dynamical WIM applications aimed at estimating the axle and wheel loads of a generic train composition by means of indirect track measurements. The new approach allows the axle loads estimation at high vehicle speeds and can be customized for several input track measurements (rail shear, rail bending, vertical forces on the sleepers, etc.) as well as a combination of them. Consequently, it can be employed in different kinds of measurement stations. Having once studied the accuracy of the algorithm in estimating the loads, the same novel procedure is used to estimate the center-of-gravity position of the railway vehicle to avoid dangerous imbalances. The algorithm can receive as inputs both experimental and simulated data; simulated data are fundamental to test the algorithm (in terms of accuracy and robustness) under any operating conditions when experimental data are not available. A wide simulation campaign has been carried out to test the algorithm performances, obtaining promising results. In the near future, the proposed approach will be validated through suitable data coming from experimental tests organized in collaboration with Ansaldo STS and ECM SpA, which are the industrial partners of this research project.

Many dynamic simulators have been developed in the last thirty years for different types of vehicles. Flight simulators and drive simulators are very well known examples. This paper describes the design and implementation of a dynamic simulator for the testing of inertial sensors devoted to vehicle navigation through a Hardware-In-The-Loop test rig composed of an industrial robot and a commercially available Inertial Measurement Unit (IMU). The authors are developing an innovative localization algorithm for railway vehicles which integrates inertial sensors with tachometers. The opportunity to set up a testing simulator capable of replicating in a realistic fashion the dynamic effects of the vehicle motion on inertial sensors allows to avoid expensive on board acquisitions and to speed up algorithm tuning. The real-time control architecture featured by the available industrial robot allows to precisely specify and execute motion trajectories with tight path and time law constraints required by the application at hand.

The execution of positioning tasks by using image-based visual servoing can be easier if a trajectory planning mechanism exists. This paper deals with the problem of generating image plane trajectories (a trajectory is made of a path plus a time law) for tracked points in an eye-in-hand system which has to be positioned with respect to a fixed object. The generated image plane paths must be feasible i.e. they must be compliant with rigid body motion of the camera with respect to the object so as to avoid image jacobian singularities and local minima problems. In addition, the image plane trajectories must generate camera velocity screws which are smooth and within the allowed bounds of the robot. We show that a scaled 3D motion planning algorithm can be devised in order to generate feasible image plane trajectories.

In this paper, a novel adaptive visual feedback scheme is presented to solve the problem of controlling the relative pose between a robot camera and a rigid object of interest. By exploiting nonlinear controllability properties, uniform asymptotic stability in the large of the image reference set-point is proved using Lyapunov's direct method. Moreover, uniform boundedness of the whole state vector is ensured by using an adaptive nonlinear control scheme, in case of unknown object depth. Experimental results with a six-degree-of-freedom robot manipulator endowed with a camera on its wrist validate the framework.

This paper focuses on the problem of controlling dynamic look-and-move systems, taking into account the robot dynamics in the visual control loop. In the case of interconnection to a linear robot subsystem, the problem of local feedback stabilization is solved by using the backstepping approach. Local stability of the equilibrium of the whole system is ensured under the assumption that the linear subsystem is minimum phase of relative degree one. A case study is also reported to validate the developed control design: a PUMA robot including its local controller is approximated by a diagonal linear subsystem and experimental results are shown with the robotic system in eye-in-hand configuration.

This paper focuses on the problem of controlling the relative position between a moving target and an autonomous nonholonomic vehicle. This problem represents a meaningful case study belonging to the class of multirate nonlinear control systems. A multi-level stabilizing control system is synthesized in continuous-time, based on a detailed analytic model of the vehicle, including the robot kinematics and nonholonomic dynamics, and actuators transfer functions. The discrete-time implementation provides a multirate nonlinear digital controller. Simulations in both continuous and discrete-time domain highlights interesting performance variations effects arising from different choices of the sampling frequencies.

We investigate the exploitation of linear models of camera-object interaction for an efficient modeling and control of image-based visual servoing systems. The approach includes a method for coping with those representation ambiguities typical of linear interaction models which may affect both planning and control. The implementation of an eye-in-hand servoing system based on affine camera models and using image contours as relevant visual features is described and discussed. The system, including an image planner, a two-dimensional/three-dimensional (2-D/3-D) controller, and a visual analysis module, allows an intuitive specification and execution of relative positioning tasks w.r.t. still or moving rigid objects. Results of real-time experiments with a robotic platform featuring a PUMA manipulator provide a further insight into characteristics and performance of affine visual servoing systems.

We present an approach for the design and control of both reflexive and purposive visual tasks. The approach is based on the bidimensional appearance of the objects in the environment and explicitly takes into account independent object motions. A linear model of camera-object interaction is embedded in the control scheme, which dramatically simplifies visual analysis and control by reducing the size of visual representation. We describe the implementation of three visual tasks of increasing complexity, obtained with the proposed scheme and based on the active contour analysis and polynomial planning of image contour transformations. Both simulations and real-time experiments with a robotic eye-in-hand configuration are discussed, validating the approach in terms of robustness and applicability to visual navigation, active exploration and perception, and human-robot interaction.

Wavelet theory is a very powerful tool for the analysis and synthesis of signals. In particular, the Haar basis is adopted, the computational effort required by the wavelet transform, is not high and thus suitable for real-time implementations even when low computing power is available. We investigate the application of a wavelet-based controller to a mechatronic drill for orthopaedic surgery. The penetration velocity of the drill is generated on the basis of the wavelet analysis of the thrust force signal and the controller is capable of fulfilling three different tasks corresponding to different specifications of the hole to be done in a long bone. Results from real experimental data are presented and discussed.

We propose a novel design for a teleoperated hyper-redundant snake robot. The kinematic structure, composed of links serially connected by revolute joints, allows it to move in a three-dimensional space. Configuration control is obtained by actuation cables and passive springs. Locomotion is based on a traveling wave lying in a vertical plane orthogonal to the support surface. The robot is able to operate in narrow sites and partially unstructured environments, where obstacles, such as stairs, inclined planes and gaps, are present. The paper focuses on the design issues related to the mechanical implementation and the kinematic control of locomotion.

In this paper, a framework for vision-based relative positioning called affine visual servoing (AVS) is presented, in which the changes in shape of image contours are used in order to control the positioning process. A feedforward control strategy complements the feedback loop, thus enhancing both speed and the overall performance of the system. The full linearization of the visual servoing problem results in a dramatical reduction of the computational burden for both the control and vision subsystems. Good simulation results with stable behavior show that the approach may be successfully applied for the design of complex positioning tasks, such as navigating by means of natural landmarks, or mimicking human gestures.

The control of exploratory and manipulative procedures in teleoperation and virtual environments requires the availability of adequate advanced interfaces capable not only of recording the movements of the human hands and arms, but also of replicating sensations of contact and collisions. In this paper the problem of replicating external forces acting against the remote/virtual arm is addressed. The design of an arm exoskeleton system developed in the authors' laboratory is presented. The exoskeleton consists of a 7 DOF actuated and sensorized mechanical structure wrapping up completely the human arm and directly supported by the shoulders and the trunk of the human operator. Emphasis is given to the implemented control procedures and to the description of the transputer-based control architecture.>

This paper reports the current state-of-the-art in medical robotics. Three general areas of advanced robotics are identified: macro robotics, micro robotics and bio-robotics. Macro robotics include the development of robots, wheelchairs, manipulators for rehabilitation as well as new more powerful tools and techniques for surgery. Micro robotics could contribute to the field of minimally invasive surgery as well as to the development of a new generation of miniaturised mechatronic tools for conventional surgery. Bio-robotics deals with the problems of modelling and simulating biological systems in order to provide a better understanding of human physiology. According to this classification, a review on the most important past and ongoing research projects in the field is reported. Some commercial products already appeared on the marker are also mentioned, and a brief analysis of the economical potentialities of robotics in medicine is presented.>

A sensor-based robot control technique for handling non-contact/transitions in a partially unknown environment is presented. Desired contacts with the environment were handled by integrating proximity and force/torque sensing information to improve efficiency in terms of speed and safety. By detecting in advance the target surface to be reached, the algorithm plans the trajectory to impose a smooth velocity profile during the approach, as well as to maintain the impact forces at the desired level by means of force control. A smooth transition between free and constrained motion control was obtained by means of weight functions depending on the measured distance between the robot end-effector and the target to be reached.>

Describes the architecture and the components of a robot workstation designed to investigate active perception, with particular emphasis on tactile sensing procedures. The workstation is centered around a multifunctional finger-like probe equipped with different types of sensors, and a PUMA 562 manipulator to carry out exploration. The system operates under the control of a distributed architecture in which different sensory information is processed in parallel, whereas exploratory parameters (contact force, direction, velocity) are set in real time. Dedicated exploratory procedures allow to extract specific object features and to sort different objects out of a given set.>