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People affected by severe motor impairments might find difficult or impossible to perform daily life activities, such as getting dressed or fed, and, thus, require a constant presence of caregivers for assistance. In this context, robotic systems can certainly help such people in improving their life quality by providing some sort of autonomy in executing some activities and by reducing the needs of a constant presence of a caregiver. Indeed, in the recent years, the research community is devoting a great effort towards the development of suitable robotic solutions to assist people with physical disabilities, also thanks to factors such as the availability of proper devices with lower prices and higher performance and robustness. From a robotic technology perspective, the specific assistive scenario can be characterized on the basis of both the robotic system used to support the impaired person, and the Human-Machine Interface (HMI) adopted to allow the user to generate commands for the system. In particular, the HMI can rely on different types of signals, such as Electroocolugraphic (EOG), Electroencephalographic (EEG) and Electromyographic (EMG) signals, and diversified HMIs have been developed in the latest years trying to find suitable solutions for specific applications and impairments. Among the possible EEG devices, non invasive Brain Computer Interfaces (BCIs) are composed of headset with a series of electrodes to place on the scalp of the user to measures the EEG signals. These signals are then processed according to the considered brain activity patterns, i.e., motor imagery or Event Related Potentials (ERPs). 

The field of cooperation and coordination of multi-robot systems has been object of considerable research efforts in the last years. The basic idea is that multi-robot systems can perform tasks more efficiently than a single robot or can accomplish tasks not executable by a single one. Moreover, multi-robot systems have advantages like increasing tolerance to possible vehicle fault, providing flexibility to the task execution or taking advantage of distributed sensing and actuation. Such systems can be used in many applications like, e.g., exploration of an unknown environment, navigation and formation control, demining, object transportation, up to playing team games (e.g., soccer). In this framework, we have developed a behavior-based approach, namely the Null-Space-based Behavioral approach (NSB), aimed at guiding single and multiple mobile robots to achieve different missions. The NSB approach, using a hierarchy based logic to combine multiple conflicting tasks, is able to fulfill or partially fulfill the elementary tasks composing the overall mission according to their positions in the hierarchy. The NSB has been extensively studied, simulated and experimentally tested while performing several missions with different kind of vehicles (i.e. mobile robots, underwater robots and surface vessels). E.g., the NSB has been used to perform formation control, entrapping/escorting a moving target, keeping a Mobile Ad-hoc NETwork, flocking with a platoon of autonomous grounded vehicles made up of 7 Khepera II mobile robots (manufactured by K-Team).