Strategy for collaborative navigation in assistive robotics: Reducing user workload

Nowadays, physically impaired people (or people with special needs) still struggle with daily tasks when using mobility aid devices, whether for crossing doors, parking or manoeuvring. In this context, assistive robotics can offer solutions to those problems thus increasing the users' quality of life. In this work we propose a collaborative navigation strategy for predicting, and thus improving, the users' skills for driving assistive vehicles. In particular, two semi-autonomous navigation modes are presented, in which the vehicle is able to predict the user's motion intentions, reducing his/her workload. The systems were tested in a simulated environment with a population of seven volunteers, using a friendly interface and later validated in a real world scenario. Results showing that the system AIDS the user to safely navigate the environment and to decrease his/her workload are also included in this work.