A General Pipeline for Online Gesture Recognition in Human–Robot Interaction
Valeria Villani, Cristian Secchi, Marco Lippi, Lorenzo Sabattini
Abstract
Recent advances in robotics have allowed the introduction of robots assisting and working together with human subjects. To promote their use and diffusion, intuitive and user-friendly interaction means should be adopted. In particular, gestures have become an established way to interact with robots since they allow to command them in an intuitive manner. In this article, we focus on the problem of gesture recognition in human–robot interaction (HRI). While this problem has been largely studied in the literature, it poses specific constraints when applied to HRI. We propose a framework consisting in a pipeline devised to take into account these specific constraints. We implement the proposed pipeline considering, as an example, an evaluation use case. To this end, we consider standard machine learning algorithms for the classification stage and evaluate their performance considering different performance metrics for a thorough assessment.