PROGRAMMA PRIN 2022 - BANDO PRIN2022 D.D. N.104 DEL 2 FEBBRAIO 2022
TITOLO DEL PROGETTO: PRIN_SOFTNESS
CODICE CUP _CUP D53D2300101000
Budget: € 73.477
P.I. o Responsabile U.R.
Prof. Gianluca Percoco
Altre Unità di Ricerca o eventuali Sub Unità
Scuola Superiore Sant’Anna, Università di Genova
Breve descrizione del progetto
Proprioception is the sense that let us perceive the location, movement, and action of parts of the body. Thanks to proprioception, for example, we can drink a glass of water with closed eyes. Any stimulus coming from outside the body is sensed owing to exteroception, including, among others, touch and pressure. Human beings can take these senses for granted, but this is not the case for robots, especially if they are "soft” to ensure safe human-robot interaction.
Research on soft robotics is becoming increasingly important worldwide, but how soft robots can sense their bodies and interact with the external environment remains an open question and a challenge, due to their continuously deformable structure, which imposes the use of flexible and light sensors.
Stretchable strain sensors based on smart textiles or electrically conductive polymers are good candidates, being non-invasive, flexible, easy to use, and inexpensive. Common devices are piezoresistive strain sensors, whose electrical resistance changes in response to an applied mechanical stretching. The main drawbacks of these soft materials are their remarkable electromechanical hysteresis and nonlinear relaxation dynamics, which must be accurately compensated to properly exploit them as sensors.
Additionally, in general, soft robots are still produced with high manual effort: the higher the complexity of the robot, the higher the skill needed by human operators, together with the increase in time and costs for fabricating and assembling. As a consequence, a further research challenge is the automatization and production standardization of these robots. In this context, 3D printing is very promising, having the potential of fabricating soft structures with embedded actuators and sensors. This will pave the way for fully automated manufacturing of sensorized and custom-made soft robots.
SOFTNESS aims to design a 3D-printed, sensorized soft robotic arm, able to sense its spatial configuration (proprioception) and detect contact with external objects (exteroception). Both already available stretchable sensors (e.g., made of conductive textiles) and custom 3D-printed sensors, made of conductive composite materials based on a polymeric matrix, will be used. Model-based and data-driven approaches will be used to compensate for the intrinsic nonlinearity of these sensing materials, allowing for proper exploitation as strain and contact sensors. Signals provided by several sensors installed on the arm will be elaborated through an embedded device, to reconstruct the spatial configuration of the arm and the contact location of external stimuli, in real-time.
SOFTNESS will then provide a custom 3D-printed soft robotic arm with proprioception and exteroception capabilities that will enable its accurate control, which is now possible only by resorting to invasive and bulky external optical sensors that can limit the movements of the arm.
Finalità
SOFTNESS aims at developing a new generation of soft robotic arms, which rely on the latest advancements in fabrication technologies and modeling approaches for the development of integrated sensors and actuators. Examples of suitable actuation approaches are already available in the literature, and they constitute a solid wealth of knowledge that can be fully exploited through advanced fabrication technologies. On the other side, sensing still requires fundamental efforts, for the lack of suitable technological solutions that guarantee the necessary level of reliability, without affecting the arm performance
Risultati attesi
During the project development, all the partners will acquire new knowledge and data and will make them available to the international scientific communities through open-access publications and participation in international conferences. The impact is mainly on researchers working on robotics, AI, nonlinear modeling, machine learning, ergonomics, control, materials.
The partners understand that an integrated and coordinated strategy for disseminating and using the results and outcomes will be key to the project’s overall success. Therefore, dissemination, exploitation, and communication activities will serve as the driving force to achieve the expected impacts.
Providing information to the identified stakeholder groups will ensure that SOFTNESS is known by the relevant stakeholders, end-users, scientific community, and policymakers. This will also strengthen collaboration links and help to establish and reinforce a wider networking activity.
risultati raggiunti (questa sezione non sarà compilata per i progetti PRIN 2022 oggetto di scorrimento, in quanto tuttora in corso)