In the last decade, several studies have proposed solutions to prototype a smart walker. Several approaches may vary from user-guided walkers with an intelligent braking system to autonomous platforms featured by people detection modules and remote teleoperations. However, despite the technological and scientific efforts, to date the translational impact of the current smart walkers is still limited. We identify three main reasons for that: i) current approaches lack reliability and robustness—especially in daily life operations and in natural scenarios; ii) the coupling between humans and machines is underestimated. The user is guided or s/he autonomously drives the walker; in most cases the integration of the intentions of the two actors (user and machine) is minimal; iii) the cost of the platform is often prohibitive and this definitely jeopardizes the vast adoption of the technology, and especially, it prevents a continuous personal usage at home. As a direct consequence, users—and in particular older adults—do not trust the walker, and thus, they do not use it.  In the EasyWalk project we hypothesize that such a trust can be achieved by providing a walker that is low-cost, easy-to-use, reliable and able to infer, to integrate and to contextualize the user's intentions according to the environment information.

Funding Programme: PRIN - PNRR
Total Fund: 260K €
Role: Partner - Local P.I.
Dates: 11/2023 - 11/2025