Using social cues to estimate possible destinations when driving a robotic wheelchair

Approaching a group of humans is an important navigation task. Although many methods have been proposed to avoid interrupting groups of people engaged in a conversation, just a few works have considered the proper way of joining those groups. Research in the field of social sciences have proposed geometric models to compute the best points to join a group. In this article we propose a method to use those points as possible destinations when driving a robotic wheelchair. Those points are considered together with other possible destinations in the environment such as points of interest or typical static destinations defined by the user´s habits. The intended destination is inferred using a Dynamic Bayesian Network that takes into account the contextual information of the environment and user´s orders to compute the probability for each destination.