Can Bayes help Disabled Users? Bayesian Plan Recognition and Shared Control to Steer the Wheelchair Sharioto

Many elderly and disabled people experience difficulties when maneuvering an electric wheelchair. Additionally, many users are not prescribed a standard electric wheelchair because they lack the necessary cognitive skills or their impairment prevents them from steering an electric wheelchair safely. In order to expand the potential group of electric wheelchairs users and in order to make wheelchair driving a safer and more comfortable experience, there has long been the claim to equip wheelchairs with some form of intelligent controller assisting in difficult or unsafe situations. It has been observed that every user presents different symptoms defining a specific driving pattern. Therefore, if the user is to be helped and not frustrated, his/her particular driving behavior should be taken into account when assisting him/her. Addressing the previous requirement, this paper presents a two step, user-centered approach to shared wheelchair control for our electric wheelchair Sharioto. The framework continuously estimates the user’s plan explicitly before trying to assist him or her (step 1). Uncertainty on the user signals and on the user’s intention is taken into account using a Bayesian approach. This approach can be tailored to the user’s specific driving characteristics. The actual navigation assistance is performed by a fine motion planner that takes the kinodynamic constraints of the wheelchair into account (step 2). As a case study, we analyze the driving behavior of a user who cannot steer to the left and show that he can drive to the left when he intends to.