On Inferring Intentions in Shared Tasks for Industrial Collaborative Robots

Abstract

Inferring human operators’ actions in shared collaborative tasks plays a crucial role in enhancing the cognitive capabilities of industrial robots. In all these incipient collaborative robotic applications, humans and robots not only should share space, but also forces and the execution of a task. In this article, we present a robotic system that is able to identify different human’s intentions and to adapt its behavior consequently, only employing force data. In order to accomplish this aim, three major contributions are presented: a) a force based operator’s intention recognition system based on data from only two users; b) a force based dataset of physical human-robot interaction; and c) validation of the whole system with 15 people in a scenario inspired by a realistic industrial application. This work is an important step towards a more natural and user-friendly manner of physical human-robot interaction in scenarios where humans and robots collaborate in the accomplishment of a task.