In the last decade, more than 700 million people are affected by disability or handicap. In this context, the research interest in assistive robotics is growing up. For people with mobility impairments daily life operations, as dressing or feeding, require the assistance of dedicated people; thus, the use of devices providing independent mobility can have a large impact on improving their life quality. 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 based on 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 ElectroOculoGraphic (EOG), ElectroEncephaloGraphic (EEG) and ElectroMyoGraphic (EMG), and diversified HMIs have been developed in the latest years trying to find suitable solutions for specific applications and impairments. From the user perspective, the operation mode of such systems may depend on the level of autonomy provided by/required to the robotic system; from the device perspective, this correspond to different control modes that vary from shared to supervisory control. In shared mode the user is involved in the control loop of the system by continuously generating high-frequency motion commands; such commands are then translated from the control software in low-level functions after applying all the safety policies. In supervisory mode the user provides high level low-frequency commands (e.g., to start/stop actions) and the system operates in complete autonomy; the control software must generate motion directives that realize the required action while taking into account safety, ...


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    Title :

    Control Methodologies for Assistive Robots Operated via Brain Computer Interface



    Publication date :

    2021-06-22


    Type of media :

    Theses


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



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