Mihai Dragusanu (University of Siena) receives the “Most promising researcher in robotics” award

The palm went to Mihai Dragusanuresearcher in Mechanics Applied to Machines of the department of Information engineering and mathematical sciences of the University of Sienafor a project that aims to create a Modular exoskeletal suit for the upper limbs, to be used in the rehabilitation and assistive field, using innovative techniques in design and control. Assistive and rehabilitative technology is essential to improving the lives of people with disabilities. However, upper limb devices, such as exoskeletons and exoskeleton gloves, are often bulky and difficult for the end user to use. Designing lightweight exoskeletons with adequate dexterity and adaptability is an open challenge. One solution is the modular exoskeletal suit for the upper limbs designed by Dragusanu, which uses the force generated through the phenomenon of twisting two strings (Twisted-String-Actuator) to activate the joints of the upper limb. Using TSA with the modular suit offers advantages in terms of comfort, high power-to-weight ratio, low cost, high precision in movements and reduces fatigue during prolonged use.

Here are the other 9 finalists:

Gloria Beraldo, Institute of Cognitive Sciences and Technologies, CNR. AI-based services to enhance commercial social robots to personalize interactions with different users (including frail ones), so as to promote active aging of elderly people living at home and in healthcare residences; facilitate interaction with the external environment for people with motor disabilities who communicate via brain-machine interfaces; help pediatric patients overcome hospitalization.

Alessandro Bertagnon, University of Ferrara. The goal of his Aurora project is to create a robotic system capable of autonomously performing vascular ultrasound screening. The first prototype uses a collaborative anthropomorphic robot that moves the ultrasound probe over the patient. The control of the robotic system is entrusted to an AI algorithm.

Luigi Borzì, Polytechnic of Turin. His project provides continuous, non-intrusive monitoring of movement disorders in daily life. A single, self-contained, waist-worn device is used to collect movement data that is analyzed to comprehensively characterize physical activity, assess postural instability, fall risk, and response to treatment.

Alessio Burrello, Polytechnic of Turin. Miniature autonomous unmanned aerial vehicles (UAVS) are gaining popularity due to their small size, which allows them to perform new tasks, such as navigating indoors or tracking people. However, their size and simplicity of electronics pose serious problems in implementing advanced intelligence on board. The project proposes a new automatic optimization pipeline for visual pose estimation using deep neural networks (DNNs).

Alessio Caporali (PhD student), University of Bologna. The objective of the project is to improve the perception and manipulation capabilities of robotic systems by leveraging artificial intelligence-based techniques to address the intrinsic difficulties associated with deformable objects, characterized by complex appearances, high-dimensional state spaces and non-linear dynamics.

Alessio Fagioli, Unitelma Sapienza. The project develops new deep learning (DL) architectures by combining neuroscience and computer science knowledge to improve models that solve heterogeneous computer vision problems, such as medical image analysis or object recognition.

Martina Lippi, Roma Tre University. The project develops robotic solutions to create a collaborative human-multi-robot paradigm for precision agriculture in permanent crops that creates a synergy that enriches robotic capabilities with greater human cognitive capabilities, making the overall system flexible, adaptive and capable to operate in complex or unpredictable situations, where robots alone would fail.

Francesco Marchetti (PhD student), University of Florence. Autonomous driving project. To navigate the streets, a self-driving car must be able to perceive the road scenario: it is essential not only to understand where critical moving agents (such as pedestrians) are located, but also to predict how they will behave and move in future.

Pietro Mascagni, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome. The collaboration, between Rome and Strasbourg, with surgeons and computer scientists to produce SDS (surgical data science) solutions for safe laparoscopic cholecystectomy has led to several reference publications in the surgical and medical imaging fields and the organization of scientific and educational events on behalf of important scientific societies. Mascagni recently established a laboratory dedicated to video-based evaluation and computer-assisted interventions at Gemelli in Rome, where he is currently specializing in surgery.