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.

Highlights

  • There is a rising trend towards smart factories where all the involved entities cooperate and communicate with each other

  • The authors stated that most of the current real applications of industrial robots are based on the cooperation levels coexistence and synchronized [9,10]

  • Due to the lack of similar existent datasets, we present a novel dataset containing force based information extracted from natural human–robot interactions

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Summary

Introduction

There is a rising trend towards smart factories where all the involved entities cooperate and communicate with each other. This is often referred to as Industry 4.0 or the fourth industrial revolution. In the interest of overcoming those safety issues, over the last few years, collaborative robots or cobots have emerged [3,4,5]. Scenarios where humans and robots exchange forces and share the execution of a task require the use of robots equipped with complex cognitive capabilities [7].

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