The population of the advanced countries is ageing, with the direct consequence that an increasing number of people will have to live with sensitive, cognitive and physical disabilities. People with impaired physical ability are not confident to move alone, especially in crowded environment and for long journeys, highly reducing the quality of their life. We propose a new generation of robotic walking assistants whose mechanical and electronic components are conceived to optimize the collaboration between the robot and its users. We will apply these general ideas to investigate the interaction between older adults and a robotic walker, named FriWalk, exploiting it either as a navigational or as a rehabilitation aid.
For the use of the FriWalk as a navigation assistance, the system guides the user securing high levels of safety, a perfect compliance with the social rules and non-intrusive interaction between human and machine. To this purpose, we developed several guidance systems ranging from completely passive strategies to active solutions exploiting either the rear or the front motors mounted on the robot. The common strategy at the basis of all the algorithms is that the responsibility of the locomotion belongs always to the user, both to increase the mobility of elder users and to enhance their perception of control over the robot. This way the robot intervenes only whenever it is strictly necessary not to mitigate the user safety. Moreover, the robotic walker has been endowed with a tablet and graphical user interface (GUI) which provides the user with the visual indications about the path to follow. Since the FriWalk was developed to suit the needs of users with different deficits, we conducted extensive human-robot interaction (HRI) experiments with elders, complemented with direct interviews of the participants. As concerns the use of the FriWalk as a rehabilitation aid, force sensing to estimate the torques applied by the user and change the user perceived inertia can be exploited by doctors to let the user feel the device heavier or lighter. Moreover, thanks to a new generation of sensors, the device can be exploited in a clinical context to track the performance of the users' rehabilitation exercises, in order to assist nurses and doctors during the hospitalization of older adults
