Abstract:
Electric wheelchairs give otherwise immobile people the freedom
of movement, they significantly increase independence
and dramatically increase quality of life. However the physical
control systems of such wheelchair can be prohibitive for
some users; for example, people with severe tremors. Several
assisted wheelchair platforms have been developed in
the past to assist such users. Algorithms that assist specific
behaviors such as door − passing, follow − corridor, or
avoid − obstacles have been successful. Recent research has
seen a move towards systems that predict the users intentions,
based on the users input. These predictions have been typically
limited to locations immediately surrounding the wheelchair.
This paper presents a new assisted wheelchair driving system
with large scale intelligent intention recognition based on
POMDPs (Partially Observable Markov Decision Processes).
The systems acts as an intelligent agent/decision-maker, it
relies on minimal user input; to predict the users intention
and then autonomously drives the user to his destination.
The prediction is constantly being updated as new user input
is received allowing for true user/system integration. This
shifts the users focus from fine motor-skilled control to coarse
control intended to convey intention.
