  Population ageing and pandemics recently demonstrate to cause isolation of
elderly people in their houses, generating the need for a reliable assistive
figure. Robotic assistants are the new frontier of innovation for domestic
welfare, and elderly monitoring is one of the services a robot can handle for
collective well-being. Despite these emerging needs, in the actual landscape of
robotic assistants there are no platform which successfully combines a reliable
mobility in cluttered domestic spaces, with lightweight and offline Artificial
Intelligence (AI) solutions for perception and interaction. In this work, we
present Marvin, a novel assistive robotic platform we developed with a modular
layer-based architecture, merging a flexible mechanical design with
cutting-edge AI for perception and vocal control. We focus the design of Marvin
on three target service functions: monitoring of elderly and reduced-mobility
subjects, remote presence and connectivity, and night assistance. Compared to
previous works, we propose a tiny omnidirectional platform, which enables agile
mobility and effective obstacle avoidance. Moreover, we design a controllable
positioning device, which easily allows the user to access the interface for
connectivity and extends the visual range of the camera sensor. Nonetheless, we
delicately consider the privacy issues arising from private data collection on
cloud services, a critical aspect of commercial AI-based assistants. To this
end, we demonstrate how lightweight deep learning solutions for visual
perception and vocal command can be adopted, completely running offline on the
embedded hardware of the robot.
