Anticipative Shared Control for Robotic Wheelchairs Used by People with Disabilities

Patients with neurological disorders are often required to cope with off-putting and longer rehabilitation process and some of them become wheelchair users with severe restriction on the arms and hands skill. Many studies have proposed solutions for autonomous or semi-autonomous powered wheelchairs focusing on navigation problems. In this project, we are interested in bringing up a planning shared control model for wheelchair to be used by people with disabilities or inexpert users to move from a room to another into an indoor place. The main objective is to reduce the effort of the users on controlling the wheelchair on these dedicated paths. This leads us to improve an algorithm of shared control to use other data sources such as agendas, travelled path, pose of the wheelchair, and time of day to infer patterns of conduction, in order to anticipate the conductor's intentions, for example, his/her intended path or final destination and to communicate with the user providing smart suggestions during the process. This anticipative shared control is of prime importance when tiring human-machine interfaces such as BCI, eye-tracking or EMG are being employed.