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This work presents the main steps of design and testing of a novel haptic interface and adaptive admittance control scheme for optimal regulation of the human–machine interaction in hand rehabilitation mediated by a smart system in virtual–reality environment. The prototype development is the result of an integrated HW/SW design and, moreover, the advantages from additive manufacturing techniques and mechanical properties of soft materials are exploited for the realization steps. Indeed, to make the interface smart, a network of piezo-resistive force sensors is embedded into the user’s command interface and the acquired signals are used for the adaptive regulation of human–machine interaction. Another distinctive feature of the haptic interface, which enables to identify this latter as a smart system, is the interaction control based on the estimation of the user’s intention within a novel scheme of adaptive admittance control. The enhanced training process in rehabilitation assisted by the haptic interface and virtual environment has been experimentally validated during a series of goal-directed tasks. The improvement of the motor performance of the user under the assistance of the adaptive admittance control has been experimentally evaluated. Further results show that the rehabilitation system supports the quantitative assessment of the robustness of the motor learning performance of the hand under the generation of haptic disturbances.

In recent years, the exploitation of Additive Manufacturing technologies for the fabrication of different kinds of sensors has abruptly increased: in particular, a growing interest for extrusion-based techniques has emerged. This research proposes the exploitation of Fused Filament Fabrication (FFF) process and two commercial materials (one flexible and one conductive) for the monolithic fabrication of a bendable, coplanar capacitive sensor. The whole sensor, consisting of a flexible substrate and two electrodes, has been fabricated in a single-step printing cycle: Design for Additive Manufacturing approach was used, setting out a methodology to direct 3D print thin and close tracks with conductive materials, in order to obtain high capacitance values measurable by common measurement instrumentations. Despite a huge exploitation of FFF technology for piezoresistive-based sensors, this manufacturing process has never been used for the fabrication of coplanar capacitive sensors since the manufacture of thin and close conductive tracks (key requirement in coplanar capacitive sensors) is a challenging task, mainly due to low manufacturability of extruded conductive beads with a high level of detail. Two versions of the sensor were developed: the first one with an embedded 3D printed coverage (ready to use) and the second one which requires a further manual post-processing to seal the electrodes. The main benefits related to the exploitation of FFF technology for these sensors are: i) the reduction of the number of different manufacturing processes employed, from at least two in traditional manufacturing approach up to one, ii) the exploitation of a cost-effective technology compared to traditional high-cost technologies employed (i.e. lithography, inkjet etc.) iii) the reduction of manual and assembly tasks (one of the proposed versions does not require any further task) , and iv) the cost-effectiveness of the sensors (in a range between 0.27 € and 0.38 €). The two developed prototypes have been tested demonstrating all their potentialities in the field of liquid level sensing, showing results consistent with the ones found in scientific literature: good sensitivity and high linearity and repeatability were proved when different liquids were employed. These 3D printed liquid level sensors have these features: i) flexible sensor, ii) the length is limited only by the machine workspace, iii) they can be either applied outside of the traditional reservoirs or embedded into the reservoirs (by 3D printing both the reservoir and sensor in the same manufacturing cycle), and iv) simple calibration.Finally, the bendability of these sensors paves the way toward their application for liquid level sensing into tanks with non-conventional shapes and for other application fields (i.e. soft robotics, non-invasive monitoring for biomedical applications).

Additive manufacturing technologies allow the fabrication of smart objects, which are made up of a dielectric part and an embedded sensor able to give real-time feedback to the final user. This research presents the characterization of a low-cost 3D-printed strain sensor, fabricated using material extrusion (MeX) technology by using a conductive material composed of a polylactic acid (PLA)-based matrix doped with carbon black and carbon nanotubes (CNT), thus making the plastic conductive. A suitable measurement set-up was developed to perform automatic characterization tests using a high repeatability industrial robot to define either displacement or force profiles. The correlation between the applied stimulus and the variation of the electrical resistance of the 3D-printed sensor was evaluated, and an approach was developed to compensate for the effect of temperature. Results show that temperature and hysteresis affect repeatability; nevertheless, the sensor accurately detects impulse forces ranging from 10 g to 50 g. The sensor showed high linearity and exhibited a sensitivity of 0.077Ωg−1 and 12.54Ωmm−1 in the force and displacement range of 114 g and 0.7 mm, respectively, making them promising due to their low cost, ease of fabrication, and possible integration into more complex devices in a single-step fabrication cycle.

The exploitation of Additive Manufacturing (AM) or 3D printing in the field of the sensor fabrication is abruptly rose in recent years. In this paper, new sensors manufactured using Fused Filament Fabrication (FFF) technology and two different commercial conductive filaments have been characterized from a thermal point of view. Using a climatic chamber to vary the temperature in a range between −5 °C and 50 °C, several tests were carried out showing a strong link between resistance and temperature changes. In particular, a positive correlation between resistance and temperature occurs. Different aspects due to the nature of the conductive 3D printed materials, nonconductive support structure, and the role of the air have been outlined, proving the need for subsequent thermal tests in order to exploit these low-cost devices as temperature sensors in the future.

In this paper a low-cost load cell with four embedded strain gauges has been developed using Fused Deposition Modeling (FDM) technology. Two commercial materials, conductive and non-conductive, have been used to manufacture the sensor in a single and non-stop printing cycle. Afterwards, each strain gauge has been characterized by evaluating the resistance change in relation to the applied force and as a consequence, it has been found that they are sensible to deformations due to compression and tension. Hence, it has been proved that with this manufacturing approach it is possible to integrate sensitive elements such as strain gauges into nonsensitive elements to create low-cost sensors using FDM, one of the most common 3D printing technology.

In the 21st century, robotics has been revolutionized by a new perspective: robots made of soft materials mimicking nature show several advantages compared to hard robot counterparts, leading to the birth and quick spread of a new scientific field named soft robotics. Due to the unconventional materials used in soft robotics (not only soft materials but also conductive, magnetic, and other materials employed for soft robot actuation), the manufacturing process is the basis by which to obtain soft structures able to meet specific requirements and save time and cost. The present paper aims to give a review of the current use of additive manufacturing (AM) methods for the manufacturing of soft robots. AM, also known as 3D printing, is characterized by several features, such as the possibility to easily produce very complex geometries, which are well suited for soft robot fabrication. The authors, after providing a summary of the most used actuation systems in soft robots, classify the use of AM technologies in soft robotics, investigating the most important and recent works in this field, as a function of how these technologies are employed in the whole soft robot manufacturing cycle. With this in mind, the authors found three approaches to exploit AM in soft robotics: rapid mold fabrication (AM plays a passive role), hybrid (AM plays an active role but manufacturing technologies other than AM are still used), and total additive manufacturing (only AM technologies are used). Only the latter approach takes full advantage of AM, although the other two still provide benefits. With new developments in commercial 3D printing systems (machines and materials) aimed at the fabrication of soft and unconventional parts, AM is set to become the manufacturing technology of the future in the soft robotics field, overcoming traditional manufacturing methods such as molding and soft lithography.