Softness and texture high-frequency information represent fundamental haptic properties for every day life activities and environment tactual exploration. While several displays have been produced to convey either softness or high-frequency information, there is no or little evidence of systems that are able to reproduce both these properties in an integrated fashion. This aspect is especially crucial in medical tele-operated procedures, where roughness and stiffness of human tissues are both important to correctly identify given pathologies through palpation (e.g. in tele-dermatology). This work presents a fabric yielding display (FYD-pad), a fabric-based tactile display for softness and texture rendering. The system exploits the control of two motors to modify both the stretching state of the elastic fabric for softness rendering and to convey texture information on the basis of accelerometer-based data. At the same time, the measurement of the contact area can be used to control remote or virtual robots. In this paper, we discuss the architecture of FYD-pad and the techniques used for softness and texture reproduction as well as for synthesizing probe-surface interactions from real data. Tele-operation examples and preliminary experiments with humans are reported, which show the effectiveness of the device in delivering both softness and texture information.

In this paper, we present a method to reconstruct the configurations of kinematic trees of rigid bodies not using measurements of relative angles (such as, e.g. rotary encoders at joints) but absolute posture sensors (such as IMUs) along with suitable filter algorithms. We argue that the relatively larger inaccuracies shown by absolute sensors can be compensated by suitable processing, such as a passive complementary filters exploiting the Mahony-Hamel formulation. The proposed method is applicable to systems where measurements of relative angles is not feasible or convenient, or where the joint kinematics are not lower pairs: for example, human body parts or soft robotic devices. In the paper, we make explicit reference to the reconstruction of posture of the compliant, underactuated Pisa/IIT SoftHand. Quantitative comparisons with ground truth data in grasping tests are used to validate the proposed method. The resulting hardware design is mechanically robust, cheap and can be easily adapted to robotic hands with different structures, as well as to sensorizing gloves for studying human grasping strategies.

In this paper we report on the development of a modular multi-DoF F/T sensor and its use in the implementation of a sensorized object capable of multi-touch detection. The sensor is composed of six 6-axis F/T sensors spatially organized on the faces of a cube. Different calibration methods are presented to directly tackle the coupling phenomena inherent to the spatial organization of the faces and the lightweight construction of the sensor which would have, otherwise, degraded its accuracy. To assess the performances of the calibration methods, a comparison is reported with respect to the measurements obtained with a commercial force/torque sensor considered as ground truth (ATI Delta). Thanks to the modular design and the possibility to cover the sensitive faces with surface patches of different geometry, a variety of sensorized objects with different shapes can be realized. The peculiar feature that all the components of the contact wrench can be measured on each face with high accuracy, renders it a unique tool in the study of grasp force distribution in humans, with envisioned use both in neuroscience investigations and robotic applications.

In this paper a fabric yielding softness display (FYD-2) is proposed, where the stretching state is controlled using two motors, while the contact area is measured in real-time. In previous works, authors proposed a fabric-based device, with embedded contact area measurement system, which was proved to provide subjects with a compelling and naturalistic softness perception. Compared to it, FYD-2 exhibits reduced dimensions, a more accurate sensorization scheme and an increased actuation velocity, which allows to implement fast changes in the stretching state levels. These changes are mandatory, for example, to properly track typical quadratic force/area curves of real materials. Furthermore, FYD-2 is endowed with an additional degree of freedom that can be used to convey supplementary haptic cues, such as directional cues, which can be exploited to produce more immersive haptic interactions. In this work we describe the mechanical design and the mathematical model of the device. The reliability in real-time tracking of stiffness and force-area curves of real objects is also demonstrated.

This paper focuses on the estimation of the impedance for a Variable Impedance Actuator (VIA) through torque and position measurements. Despite the recent development of several VIA, impedance control is not yet implemented in closed loop because of the difficulty of obtaining in real-time measurements of time-varying impedance. The estimation algorithm is proposed as an alternative approach to the standard procedures of impedance identification, to robustly tolerate the variability of the mechanical stiffness due, for example, to model uncertainties. The impedance estimator is therefore implemented on the Actuator with Adjustable Stiffness (AwAS). The effectiveness of the proposed estimator is proved through simulation and experimental results.