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In recent years, the number of people with disabilities has increased hugely, especially in low- and middle-income countries. At the same time, robotics has made significant advances in the medical field, and many research groups have begun to develop low-cost wearable solutions. The Mechatronics and Dynamic Modelling Lab of the Department of Industrial Engineering at the University of Florence has recently developed a new version of a wearable hand exoskeleton for assistive purposes. In this paper, we will present a new regression method to predict the finger angle position of the first joint from the value of the sEMG of the forearm and the previous position of the finger itself. To acquire the dataset necessary to train the regressor a specific graphical user interface was developed which was able to acquire sEMG data from a Myo armband and the finger position from a Leap Motion Controller. Two long short-term memory (LSTM) models were compared, one in its standard configuration and the other with a convolutional layer, yielding significantly better performance for the second one, with an increase in R2 coefficient from an average value of 0.746 to 0.825, leading to the conclusion that a convolutional layer could increase performance when few sensors are available.

Coastal zones are subjected to a wide range of phenomena acting on very different temporal and spatial scales: from decades to days and from hundreds of kilometers to tens of meters. Planning the management of such areas, thus, requires an accurate and updated knowledge of the ongoing processes. While standard monitoring activities are functional for the medium-long time scale and medium-large spatial scale, they struggle to provide adequate information concerning the short period (i.e., days) and small range (i.e., few meters). In addition, such operations are affected by high costs and logistic complexity since they generally involve the deployment of specific aircraft or maritime vehicles. On the contrary, the employment of robotic devices can represent a solution to these issues. Their proper use can allow for frequent surveys and enhance the coverage of the acquired data due to optimized mission strategies. Marine robotics has the potential to arise as an efficient complementary tool to standard monitoring techniques. Nevertheless, the use of marine robots is still limited and should be improved. The purpose of this paper is to discuss the current state of robotic technology, identifying both the benefits and shortcomings of its use for micro-tidal marine-coastal monitoring. The discussion will be supported by actual results, taken as an example, achieved using FeelHippo AUV, the compact Autonomous Underwater Vehicle (AUV) developed by the Department of Industrial Engineering at the University of Florence, Italy.

Recently, robotics has increasingly become a companion for the human being and assisting physically impaired people with robotic devices is showing encouraging signs regarding the application of this largely investigated technology to the clinical field. As of today, however, exoskeleton design can still be considered a hurdle task and, even in modern robotics, aiding those patients who have lost or injured their limbs is surely one of the most challenging goal. In this framework, the research activity carried out by the Department of Industrial Engineering of the University of Florence concentrated on the development of portable, wearable and highly customizable hand exoskeletons to aid patients suffering from hand disabilities, and on the definition of patient-centered design strategies to tailor-made devices specifically developed on the different users’ needs. Three hand exoskeletons versions will be presented in this paper proving the major taken steps in mechanical designing and controlling a compact and lightweight solution. The performance of the resulting systems has been tested in a real-use scenario. The obtained results have been satisfying, indicating that the derived solutions may constitute a valid alternative to existing hand exoskeletons so far studied in the rehabilitation and assistance fields.