A Robust Real-Time 3D Tracking Approach for Assisted Object Grasping

Robotic exoskeletons are being increasingly and successfully used in neuro-rehabilitation therapy scenarios. Indeed, they allow patients to perform movements requiring more complex inter-joint coordination and gravity counterbalancing, including assisted object grasping. We propose a robust RGB-D camera-based approach for automated tracking of both still and moving objects that can be used for assisting the reaching/grasping tasks in the aforementioned scenarios. The proposed approach allows to work with non pre-processed objects, giving the possibility to propose a flexible therapy. Moreover, our system is specialized to estimate the pose of cylinder-like shaped objects to allow cylinder grasps with the help of a robotic hand orthosis. To validate our method both in terms of tracking and of reaching/grasping performances, we present the results achieved conducting tests both on simulations and on real robotic-assisted tasks performed by a patient.