Dynamic Movement Primitives for Human-Robot interaction: Comparison with human behavioral observation

Abstract

This article presents the current state of an ongoing work on Human-Robot interaction in which two partners collaborate during an object hand-over interaction. The manipulator control is based on the Dynamic Movement Primitives model, specialized for the object hand-over context. The proposed modifications enable finer control of the dynamic of the DMP to align it to human control strategies, where the contributions of the feedforward and feedback parts of the control are different to the original DMP formulation. Furthermore, the proposed scheme handles moving goals. With these two modifications, the model no longer requires an explicit estimation of the exchange position and it can generate motion purely reactively to the instantaneous position of the human hand. The quality of the control system is evaluated through an extensive comparison with ground truth data related to the object interaction between two humans acquired in the context of the European project CogLaboration which envisages an application in an industrial setting.