Navigation system using passive collaborative control adapted to user profile for a rollator device

Abstract

Rollators provide autonomy to persons with mobility impairments. These platforms can be used while people perform their Activities of Daily Living in order to provide support and/or balance. Also, they can be used during the rehabilitation process to strengthen the lower limbs or to provide balance before users can progress to canes or crutches.

Rollators have a limited set of personalization options, but they are usually related to the users' body size. Hence, people who need extra typically have to choose a wheelchair instead. This transition to a wheelchair limits users' movements and it increases their disuse syndrome because they do not exercise their lower limbs. Hence, it is a priority to extent the use of rollator platforms as much as possible by adapting help to people who can not use a conventional rollator on their own.

Technological enhancements can be added to rollator to expand their use to a larger population. For example, force sensors on handlebars provide information about users' weight bearing. This information can be used during rehabilitation to control their partial weight-bearing. Encoders on wheels may also provide useful information about the walking speed, which is a well know estimator of fall risk. In addition to monitorization, motors can be attached to the wheels for assistance, e.g. to reduce effort while ascending slopes.

This thesis focuses on creating a navigation system for a robotized rollator, which includes weight bearing sensors, encoders and wheel motors. The navigation system relies on passive collaborative control to continuously combine user and system commands in a seamless way. The main contribution of this work is adaptation to the user's needs through continuous, transparent monitorization and profile estimation.