Abstract
The elderly population has rapidly increased in past years, bringing huge demands for elderly serving devices, especially for those with mobility impairment. Present assistant walkers designed for elderly users are primitive with limited user interactivity and intelligence. We propose a novel smart robotic walker that targets a convenient-to-use indoor walking aid for the elderly. The walker supports multiple modes of interactions through voice, gait or haptic touch, and allows intelligent control via learning-based methods to achieve mobility safety. Our design enables a flexible, initiative and reliable walker due to the following: (1) we take a hybrid approach by combining the conventional mobile robotic platform with the existing rollator design, to achieve a novel robotic system that fulfills expected functionalities; (2) our walker tracks users in front by detecting lower limb gait, while providing close-proximity walking safety support; (3) our walker can detect human intentions and predict emergency events, e.g., falling, by monitoring force pressure on a specially designed soft-robotic interface on the handle; (4) our walker performs reinforcement learning-based sound source localization to locate and navigate to the user based on his/her voice signals. Experiment results demonstrate the sturdy mechanical structure, the reliability of multiple novel interactions, and the efficiency of the intelligent control algorithms implemented. The demonstration video is available at: https://sites.google.com/view/smart-walker-hku.
Highlights
Over the last few decades, the elderly population has rapidly increased globally and is expected to exceed 2 billion by 2050 (WHO, 2018)
This paper proposes a novel smart robotic walker platform to assist the elders with mild mobility impairment
We design a comprehensive finite-state machine model to detect user intention and emergency events in a timely manner through analyzing spatiotemporal pressure data collected from soft handle
Summary
Over the last few decades, the elderly population has rapidly increased globally and is expected to exceed 2 billion by 2050 (WHO, 2018). We argue that intelligence is essential for an elderly walker to detect abnormal user behaviors and provide timely safety support, since primitive assistance devices, such as rollators and walkers, are much likely to fail (Bertrand et al, 2017). Rather than merely using remote button (Glover, 2003), voice (Gharieb, 2006), or gesture (Gleeson et al, 2013) to achieve user interaction, older persons need various modes of human-robot interaction for convenience and efficiency. These motivate us to seek a solution of equipping the robotic walker with sufficient intelligence and interaction to guarantee mobility safety of older users. (4) Autonomous mobility through RL to locate the user (sound source) and navigate to the user, in a multi-room household with environmental noises, reverberations, and long distance (over 10 m)
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