Towards a User Adaptive Assistive Robot: Learning from Demonstration Using Navigation Functions

Elderly and mobility impaired people need special attention during bathing activities, since these tasks are demanding in body flexibility. Our aim is to build an assistive robotic bathing system, in order to increase the independence and safety of this procedure. Towards this end, the expertise of professional carers for bathing sequences and appropriate motions have to be adopted, in order to achieve natural, physical human - robot interaction. In this paper a Navigation Function (NF) approach is proposed in order to reproduce the way an expert clinical carer executes the bathing activities by means of construction repulsive potential fields ("virtual obstacles") for an assistive bath robot. The produced vector field, constructed based on the demonstration procedure, is used for real-time motion behavior planning tasks, which exploits the visual information from Depth sensors and the advantages of the NF approach, to estimate the reference pose for the end- effector of the assistive robotic system. The proposed method guarantees globally asymptotic convergence to the learned from demonstration washing motion, within the deformable and moving body-part limits, while in addition, restricted areas on the body surface are avoided. The proposed method is evaluated using real experimental data, obtained from human subjects during pouring water task demonstration.