Marvin: an Innovative Omni-Directional Robotic Assistant for Domestic Environments

Technology is progressively reshaping the domestic environment as we know it, enhancing home security and the overall people well-being through smart connected devices. However, 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 only one of the possible services an intelligent robotic platform can handle for collective well-being. Despite these emerging needs, the actual landscape of robotic assistants lacks a platform which successfully combine a reliable and agile 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 service functions: monitoring of elderly and reduced-mobility subjects, remote presence and connectivity, and night assistance. With respect to previous works, we propose a tiny size omnidirectional platform, which enable a more agile mobility and an effective obstacle avoidance. Moreover, we introduce a controllable positioning device, which easily allows the user to access the visual interface, and, at the same time, it can physically extend the field of view 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.