Floating photovoltaic systems represent a promising solution for renewable energy generation, offering an alternative to agricultural land consumption. However, these installations have the potential to exert an effect on the aquatic ecosystem, emphasizing the necessity of effective monitoring strategies also related to system management issues. In this paper, the use of an unmanned surface vehicle, which can also operate as an autonomous surface vehicle, is proposed to overcome many difficulties of maintenance and monitoring in aquatic environments. A review of the extant literature reveals the scarcity of a cohesive monitoring framework for these plants, highlighting the urgent need for standardized guidelines for plant management and water quality monitoring. The implementation of automated plants directly addresses this gap by providing a tool for efficient and sustainable monitoring tasks, enabling, at the same time, aquatic ecosystem protection and energy production optimization. To address these challenges, a low-cost prototype of an autonomous surface vehicle is proposed. Preliminary test results on trajectory control and obstacle recognition are reported.

With the increasing manufacturing of electric vehicles, car battery recycling is crucial for environmental sustainability. The disassembly of car batteries includes critical health hazards for the operator, due to potential chemical reactions or physical injuries. These reasons make robots particularly interesting for automatic disassembly. This paper proposes a systematic approach to automation and human–robot cooperation in car battery disassembly tasks with a case study on screw removal. A novel parameter is proposed to evaluate whether a human operator or a robot is more appropriate for each specific task, considering both performance and associated risks. The proposed metrics are validated with an experimental example, in which the performance of a robot and a human on a screw-removal task is compared numerically using statistical methods. The advantages and disadvantages of both options are examined through the application and show how the new performance criterion effectively provides insights into the distribution of tasks between humans and robots.