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Robotic handling of objects is not always a trivial assignment, even in teleoperation where, in most cases, this might lead to stressful labor for operators. To reduce the task difficulty, supervised motions could be performed in safe scenarios to reduce the workload in these non-critical steps by using machine learning and computer vision techniques. This paper describes a novel grasping strategy based on a groundbreaking geometrical analysis which extracts diametrically opposite points taking into account surface smoothing (even those target objects that might conform highly complex shapes) to guarantee the uniformity of the grasping. It uses a monocular camera, as we are often facing space restrictions that generate the need to use laparoscopic cameras integrated in the tools, to recognize and isolate targets from the background, estimating their spatial coordinates and providing the best possible stable grasping points for both feature and featureless objects. It copes with reflections and shadows produced by light sources (which require extra effort to extract their geometrical properties) in unstructured facilities such as nuclear power plants or particle accelerators on scientific equipment. Based on the experimental results, utilizing a specialized dataset improved the detection of metallic objects in low-contrast environments, resulting in the successful application of the algorithm with error rates in the scale of millimeters in the majority of repeatability and accuracy tests.

he adaptation of machine vision solutions for motion capture has generated an interest in determining whether markerless capture methods can achieve a level of accuracy particularly similar to capture techniques with passive or active markers, being an essential factor for the identification and treatment of motor weaknesses in physiotherapeutic fields. In this sense, the aim of this work is to perform a comparison of two motion capture techniques: intrusive and non-intrusive, using the 3D tracking systems OptiTrack and MediaPipe to determine the performance of markerless pose estimation in obtaining the ranges of motion (ROM) of the upper body of a person. The capture is simulated using a virtual environment (VE) developed on the Unity platform, evaluating accuracy and deviation levels using Matlab. The non-intrusive pose estimation solution generated 92.82% average accuracy with respect to the standard trajectory when capturing the ROMs of the limb, proving to be a cost-effective and significantly accurate option for the analysis of upper body kinematics in rehabilitation exercises. The study of the elbow joint indicated similar results in flexion, with 1.382° degrees difference as did the shoulder joint, with 1.237° and 2.969° degrees in flexion and abduction, respectively. Finally, the captured ROMs demonstrate that the integration of a VE decreases the deviation in the trajectory of the limb, guiding the participant in the presented exercise

The characterization of vibrotactile perception is crucial to accurately configure haptic devices and create appropriate stimuli for improving user performance in human-machine interaction systems. This paper presents a study aiming to determine the absolute and differential vibrotactile thresholds in different areas of the torso to develop reliable haptic patterns to be displayed using a haptic vest. In the absolute threshold experiment, we measure the minimum detectable vibration using a forced-choice task. Furthermore, in the differential threshold experiment, we measure the minimum frequency change needed for users to discriminate two successive vibrotactile stimuli using a vibration matching task. The first experiment does not show differences between absolute thresholds, opening up the possibility of setting a unique minimal vibration for creating haptic patterns. Similarly, the second experiment does not show differences between differential thresholds. Moreover, as these thresholds follow Webers law, it is viable to estimate any upper or lower differential threshold for any reference stimulus using a K-value. These results are a first step for creating vibrotactile patterns over the torso with the employed eccentric rotating mass motors. Moreover, the whole study provides a method to obtain these psychophysical values since the usage of different motors can change these results.

Recovery of therapeutic or functional ambulatory capacity in patients with rotator cuff injury is a primary goal of rehabilitation. Wearable powered exoskeletons allow patients to perform repetitive practice with large movements to maximize recovery, even immediately after the acute event. The aim of this paper is to describe the usability, acceptability and acceptance of a hybrid exoskeleton for upper-limb passive rehabilitation using the System Usability Scale (SUS) questionnaire. This equipment, called ExoFlex, is defined as a hybrid exoskeleton since it is made up of rigid and soft components. The exoskeleton mechanical description is presented along with its control system and the way motion is structured in rehabilitation sessions. Seven patients (six women and one man) have participated in the evaluation of this equipment, which are in the range of 50 to 79 years old. Preliminary evidence of the acceptance and usability by both patients and clinicians are very promising, obtaining an average score of 80.71 in the SUS test, as well as good results in a questionnaire that evaluates the clinicians' perceived usability of ExoFlex.

Motion tracking techniques have been extensively studied in recent years. However, capturing movements of the upper limbs is a challenging task. This document presents the estimation of arm orientation and elbow and wrist position using wearable flexible sensors (WFSs). A study was developed to obtain the highest range of motion (ROM) of the shoulder with as few sensors as possible, and a method for estimating arm length and a calibration procedure was proposed. Performance was verified by comparing measurement of the shoulder joint angles obtained from commercial two-axis soft angular displacement sensors (sADS) from Bend Labs and from the ground truth system (GTS) OptiTrack. The global root-mean-square error (RMSE) for the shoulder angle is 2.93 degrees and 37.5 mm for the position estimation of the wrist in cyclical movements; this measure of RMSE was improved to 13.6 mm by implementing a gesture classifier.

This article describes the performance of a flexible resistive sensor network to track shoulder motion. This system monitors every gesture of the human shoulder in its range of motion except rotations around the longitudinal axis of the arm. In this regard, the design considers the movement of the glenohumeral, acromioclavicular, sternoclavicular, and scapulothoracic joints. The solution presented in this work considers several sensor configurations and compares its performance with a set of inertial measurement units (IMUs). These devices have been put together in a shoulder suit with Optitrack visual markers in order to be used as pose ground truth. Optimal configurations of flexible resistive sensors, in terms of accuracy requirements and number of sensors, have been obtained by applying principal component analysis techniques. The data provided by each configuration are then mapped onto the shoulder pose by using neural network algorithms. According to the results shown in this article, a set of flexible resistive sensors can be an adequate alternative to IMUs for multiaxial shoulder pose tracking in open spaces. Furthermore, the system presented can be easily embedded in fabric or wearable devices without obstructing the user’s motion.

The International Fusion Material Irradiation Facility-DEMO Oriented NEutron Source (IFMIF-DONES) is composed of numerous complex systems and components that need on-site maintenance. Such need requires Remote Handling (RH) operations with advanced technology that is capable of preventing exposure to radiation and complying with stringent plant requirements in hostile environments. Moreover, specific design and integration of the RH systems have to be carried out in order to properly comply with constraints and procedures for remote operations, which in most cases become an engineering challenge. This paper presents a RH methodology that covers all the necessary aspects for the entire rigorous implementation and execution of remote operation in IFMIF-DONES. The methodology is made up of a set of different stages, which are based on the initial cooperation among different teams involved in the remote operation cycle. This approach leads to an iterative process that allows optimization and improvement of remote operations. It aims at accelerating the process with safer and robust concept of maintenance, simplified procedures, minimized breakdowns and reduced cost and time.

The International Fusion Materials Irradiation Facility-DEMO Oriented Neutron Source (IFMIF-DONES) consists of complex systems and massive components that need to be on site assembled and maintained. For several of them it is required to perform maintenance, inspection and monitoring tasks over many years in a hostile environment and in efficient, safe and reliable manner. The maintenance of IFMIF-DONES’ systems and components, located mainly in the Test Systems (TS), in the Lithium Systems (LS) and in the Accelerator Systems (AS), is classified as a Remote Handling (RH) Class 1st activity and as such is considered a crucial and essential activity whose success will strictly depend on the IFMIF-DONES RH capability. According to this, a Remote Handling System (RHS) for IFMIF-DONES, which comprises the whole set of Remote Handling Equipment and tooling for the execution of maintenance tasks, has been designed. A wide range of technologies is involved: special cranes, manipulator arms, lift interface frames, special cameras, control systems and virtual reality. In this paper an overview on status of the design of the main robotic systems and tooling of the RHS of IFMIF-DONES, including design requirements, functions and maintenance tasks to be performed, is given.

The Time Domain Passivity Approach (TDPA), a method to inject adaptive damping to satisfy the passivity condition in real-time, has emerged as a powerful tool to stabilize coupled network systems with/without communication delay, such as haptic and teleoperation systems, due to its simplicity and effectiveness. However, we found that the conventional TDPA has unnecessary conservatism especially in delayed coupled network systems due to direction dependent energy calculation and dissipation. In this paper, we propose a new time domain passivity approach with reduced conservatism by considering the energy reflection from an energy storage element in the network. The method is generally formulated with a delayed 2-port network system including an energy storage element and implemented to a teleoperation system. The proposed method is experimentally tested and a comparison with the conventional TDPA reveals improved kinesthetic coupling and transparency in terms of position tracking and force reflection.