Passivity-based methods are widely used in tele-operation to guarantee stability, especially for the widely used Position-Force measured (PFm) architecture. Among them, Time Domain Passivity Approach (TDPA) achieves stability through passivation, generating a dissipation action that degrades the reference signals and thus, the performance of the system. Whereas passivization is necessary to ensure stability during contact, in free motion, it acts just as a disturb, without having a real impact on stability. In fact, during free motion the force feedback is zero, i.e. the teleoperation loop is not closed and thus, a stabilization action is not needed. Therefore, this paper proposes a formal demonstration that passivation is not needed during free motion. Accordingly, the paper introduces a new formulation of the TDPA to take into account the free motion condition. A one-degree-of-freedom case study is then proposed to provide a simple example to instantiate the formalism and to show the advantages of the proposed method, that achieve an almost total cancellation of the drift during free motion. Finally, the paper discusses the limitations of the method in real-case scenarios. In particular, how the inertia of tools mounted after the force sensors can affect the measurements and the perception of the system.

Lower Limb Exoskeletons (LLEs) are wearable robotic systems that provide mechanical power to the user. Human-exoskeleton (HE) connections must guarantee the subsistence of the user’s natural behavior during the interaction, avoiding the exertion of undesired forces, i.e., the robot must be transparent. Since transparency is an essential feature of exoskeletons’ design, numerous works focus on its maximization, e.g., employing passive joints at the HE interfaces. Given the inherent complications of repeatedly prototyping and experimentally testing a device, modeling the exoskeleton and its physical interaction with the user emerges as an extremely valuable approach for assessing the design effects. This paper proposes a novel method to compare different exoskeleton configurations with a flexible simulation tool. This approach contemplates simulating the dynamics of the device, including its interaction with the wearer, to evaluate multiple connection mechanism designs along with the kinematics and actuation of the LLE. This evaluation is based on the minimization of the interaction wrenches through an optimization process that includes the impedance parameters at the interfaces as optimization variables and the similarity of the LLE’s joint variables trajectories with the motion of the wearer’s articulations. Exploratory tests are conducted using the Wearable Walker LLE in different configurations and measuring the interaction forces. Experimental data are then compared to the optimization outcomes, proving that the proposed method provides contact wrench estimations consistent with the collected measurements and previous outcomes from the literature.

Haptic interaction often requires stabilizing controllers for safety. The Time-Domain Passivity Approach guarantees passivity (then stability) by observing and dissipating energy generated from active elements in a network. The dissipating action is performed by a Passivity Controller, whose action is commanded to the physically limited robot actuators. Thus, the controller stabilizing action should be in turn limited in order to command displayable references to the actuators. This problem is rarely taken into account in the literature and when it is, the limitation is neither directly related to the actuator power limits, nor to the robot's current configuration. The limits of the currently adopted strategies leave room for improvement. In this paper, a new strategy to limit the Passivity Controller action is proposed taking into account both the physical limits of the actuators and the robot configuration. This new strategy is experimentally tested against the classical one based on the sampling time. In the experiment, a human interacts with a virtual wall in a Virtual Environment through a haptic interface. The wall induces an unstable behavior passivated with the two limitation strategies. The results clearly state the benefits introduced by the proposed strategy in two relevant cases.

This work presents a description of the EXOSMOOTH project, oriented to the benchmarking of lower limb exoskeletons performance. In the field of assisted walking by powered lower limb exoskeletons, the EXOSMOOTH project proposes an experiment that targets two scientific questions. The first question is related to the effectiveness of a novel control strategy for smooth assistance. Current assist strategies are based on controllers that switch the assistance level based on the gait segmentation provided by a finite state machine. The proposed strategy aims at managing phase transitions to provide a smoother assistance to the user, thus increasing the device transparency and comfort for the user. The second question is the role of the actuation at the ankle joint in assisted walking. Many novel exoskeletons devised for industrial applications do not feature an actuated ankle joint. In the EXOSMOOTH project, the ankle joint actuation will be one experimental factor to have a direct assessment of the role of an actuated joint in assisted walking. Preliminary results of 15 healthy subjects walking at different speeds while wearing a lower limb exoskeleton supported the rationale behind this question: having an actuated ankle joint could potentially reduce the torques applied by the user by a maximum value of 85 Nm. The two aforementioned questions will be investigated in a protocol that includes walking on a treadmill and on flat ground, with or without slope, and with a load applied on the back. In addition, the interaction forces measured at the exoskeleton harnesses will be used to assess the comfort of the user and the effectiveness of the control strategy to improve transparency.

Lower limbs exoskeletons provide assistance during standing, squatting, and walking. Gait dynamics, in particular, implies a change in the configuration of the device in terms of contact points, actuation, and system dynamics in general. In order to provide a comfortable experience and maximize performance, the exoskeleton should be controlled smoothly and in a transparent way, which means respectively, minimizing the interaction forces with the user and jerky behavior due to transitions between different configurations. A previous study showed that a smooth control of the exoskeleton can be achieved using a gait phase segmentation based on joint kinematics. Such a segmentation system can be implemented as linear regression and should be personalized for the user after a calibration procedure. In this work, a nonlinear segmentation function based on neural networks is implemented and compared with linear regression. An on-line implementation is then proposed and tested with a subject.

Railways safety regulations require the drivers acting on a pedal to signal that they are awake and vigilant. This implies a noticeable biomechanical load on the driver. In this work, we propose an embedded computer-vision system that, using a single camera placed on the cockpit of a train, analyzes the driver's watchfulness by monitoring gaze and eyelid blinking. The proposed system provides a consensus to the control logic of the train, which replaces the action on the pedal. The system copes with the peculiar conditions of a train's cabin, such as variable illumination, the variability of the driver's face image and presence of more than one people in the cabin. At the same time, it accounts for the constraints posed by the international regulation (Safety Integrity Level IV) and customer specifications, which poses limitations on the hardware selection. The paper presents the design and evaluation of this system. The former includes the hardware selection and the algorithm development, whereas the latter includes preliminary tests for tuning the algorithm and final tests in real operating conditions for the evaluation of the system. The results show that the systems always correctly detects the driver's watchfulness and, importantly, it does not report false positives. As such, it can be used to avoid the driver's action on the pedal and reducing the biomechanical load.

The shortage of specialist caused by the increased need for medical examinations has stimulated the application of robotics technologies to telemedicine. For some of the most common medical examinations such as ultrasonography and palpation, doctors exploit haptic feedback to formulate a diagnosis. This is especially true for palpation, where haptic feedback plays the biggest role. In this paper, we present a novel 3-Degrees-of-Freedom (DoFs) robotic interface which is designed to be integrated into a telepalpation system. In particular, this haptic interface is the master of a teleoperation loop in which the slave operates on the patient. Therefore, its design allows the doctor to explore the whole patient's abdomen while providing the doctor with a haptic feedback when in contact with the patient. A preliminary assessment of the interface is also presented: three participants were asked to detect the presence and the size of a sphere without visual clues. Results show that the interface is suitable for the application in remote palpation.

For a proactive and user-centered robotic assistance and communication, an assistive robot must make decisions about the level of assistance to be provided. Therefore, the robot must be aware of the preferences and the capabilities of the elderly. At the same time, relying on a sensing setup which is totally embedded in the assistive robot would increase its usability. In the framework of the RAMCIP project, a novel skills evaluation methodology has been developed to make the robot aware of the user's perceptual, cognitive and motor skills. This paper presents such a methodology and its preliminary evaluation. Based on a task analysis of the activities for which the robot provides assistance, the user's skills are given a score which is updated at different time scales based on the source of information. Highly reliable information is gathered from caregivers at a low rate by means of a graphical interface hosted by the robot. This information refers to standard medical examinations. Based on the modules for motion tracking, object and activity recognition, specific actions of ADL are selected to update motor skills score at a higher rate, which is typically twice per day. The two sources of information are then fused in a Kalman filter. Preliminary results on the illustrative example of arm precision show that the robot's sensing and cognitive capabilities suffice to obtain a state-of-the-art evaluation of the arm precision skill.

The remote examination is becoming more and more important as the population is aging and experts lack as ever before. We propose a novel system which is suitable for remote examination and in particular for remote auscultation. The system is located at two sites, at the patient site a robot holds a stethoscope which is placed on the patient while an RGB-D sensor streams a video of the scene. At the doctor site, the doctor interacts with a haptic interface that allows s/he to move the stethoscope while receiving haptic feedback when the stethoscope is in contact with the patient and looking at the remote scene on a screen. The doctor listens to the noise from the stethoscope thanks to a diaphragm and a headset where the audio stream from the patient site is played. After presenting this novel system, we show its effectiveness by means of experiments that involve auscultation-like tasks. We show the usability of the system to place the stethoscope, the usability to hear correctly the noise of the heart as well as the overall quality of the streamed audio signal.

Nowadays robotics educational platforms play an important role in the development and testing of new robotic technologies. These systems offer at low cost the possibility to access and experiment basic robot functionalities. In this paper, we examined the KUKA youBot: an omnidirectional mobile platform equipped with a five DOFs (Degrees of Freedom) robotic arm. The current internal design of the control loops limits severely its performances.

Cardiopulmonary resuscitation (CPR) is a first-aid key survival technique used to stimulate breathing and keep blood flowing to the heart. Its effective administration can significantly increase the chances of survival in victims of cardiac arrest. In this paper, we propose a markerless system for quality CPR training based on RGB-D (RGB + Depth) sensors, called RELIVE. Then, we report the results of a series of experimental tests conducted to evaluate RELIVE tracking performance. The proposed system is able to accurately track the 3-D position of the hands performing CPR by means of RGB-D sensors to estimate the chest compression rate and depth, providing a real-time visual/audio feedback about the rescuer's performance. Finally, the system usability has been assessed by both healthcare professionals and lay people.

The shortage of physicians afflicting developed countries encourages engineers and doctors to collaborate towards the development of telemedicine. In particular, robotic systems have the potential for helping doctors making examination. A very common examination that can be the goal of a robotic system is palpation. Most of the robotics systems that have been developed for palpation present interesting features such as integrating augmented reality environments or allowing for hand free interaction. In this paper we present a novel palpation system that allows us to perform virtual palpation of real objects by means of a haptic and an augmented reality feedback. This system features an encountered-type haptic interface in which the haptic feedback is calculated by a collision detection algorithm that is based on online recording of the surface to be touched. The system allows the users to remove their hand from the haptic interface end-effector that follows the user's hand thanks to the tracking performed by a Leap Motion. We show that the system provides a natural interaction during the contact-non contact switch, a suitable force during indentation, and it allows to discriminate objects within the body through the haptic channel.

Wearable motion tracking systems represent a breakthrough in ecological motion tracking. Their effectiveness has been proved in many fields, from performance assessment to human-robot interaction. Most of the approaches are based on the exploitation of optimal probabilistic filtering of inertial motion units (IMUs) signals, ranging from linear Kalman Filters (KF) to Particle filters (PF). Since most of the models are highly nonlinear, filters such as Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) are typically used. These approaches cause all the variables of the models to be correlated each other. Probabilistic Graphical Models (PGM) are a framework for probabilistic reasoning that allows to explicitly declare the actual dependencies among variables. In this paper we propose a novel algorithm for motion tracking with IMUs based on PGM. The model is compared to the state of the art UKF algorithm in tracking the human upper limb. The results show that the proposed approach perform a slightly better compared to the UKF.

The skills professional rowing indoor training (SPRINT) system is designed to support rowing training. The system includes a configurable instrumented rowing apparatus that supports sculling and sweep rowing and that is coupled with a virtual reality display and haptic feedback. Herein, the system has been updated with models that aim at improving force rendering and at simulating the rowing dynamics. These new models support the rendering of vertical and horizontal forces on the hands and they estimate the effects that actions performed on SPRINT would produce on an actual rowing shell. A proof of concept evaluation with one expert and one intermediate rower included a comparison of data gathered on an actual boat and with SPRINT. Outputs of the boat dynamics model showed to be consistent when compared both with the literature and on-boat data. Moreover, these preliminary data suggest boat dynamics output to be useful to discriminate expertise. In addition, subjective ratings of kinematic features and force rendering by expert and intermediate rowers indicated that they find SPRINT suitable for training.

A recent trend in virtual environments aims at making the user free of devices or limitations in its motion, at the benefit of immersiveness and interactivity. This work introduces an interaction paradigm that goes beyond motion based interaction, by making use of measured real forces exerted by the user in free space. The sensation of touch with virtual object is obtained by vibrotactile stimulation combining virtual contact information with measured forces. In this way the user has an additional dimension of interactivity at the benefit of immersivity, without incurring in the reduction of sense of presence introduced by grounded haptic interfaces. This paradigm is presented and discussed in particular in the context of a boxing training simulation, as one of the possible application scenarios.