Coordinated Control of a Collaborative 6R Robotic Arm With a Virtual Twin and Augmented Reality for Engineering Education

Introduction

Today's industries require greater speed and sophistication for decision making, this new era of Digital Transformation and Artificial Intelligence makes possible truly data-driven businesses. Emerging techniques such as Industrial Internet of Things (IIoT), Cyberphysical Systems CPS), Collaborative Robots, Virtual and Augmented Reality and those related with Artificial Intelligence (Big Data and Deep Learning) can create great leaps in efficiency, meaning and knowledge in companies and in society in general. In short, it represents a great opportunity for companies to respond to the challenges of competitiveness. In this sense, according to a survey conducted in 2018 by McKinsey & Company to companies about the adoption of Artificial Intelligence (Rao & Verweij, 2017), 47% of the 2,135 participants mention having incorporated it into some business process, which means a significant increase compared to a similar study carried out in 2017 where only 20% of participants reported using this type of technology. The majority of the participants (58%) indicated that less than 10% of digital investment is destined to the development of products that incorporate AI (Artificial Intelligence), but many of those surveyed (78%) are very confident that there will be an increase in investment in AI in the coming years.

The growing popularity of collaborative robots for process automation does not come exclusively from their capabilities, but is also due to the fact that it is a competitive product, which is why many companies are betting on its implementation, which is why it is essential to know how correctly handle a collaborative robot, since when you have one, it is dangerous to use it without prior training; Currently there is a diversity of simulators, however, the physical essence of the robot is lost. Another unfavourable aspect is that the physical robot cannot be used remotely, since it is necessary to use the indicated instruments, but these tools are expensive and therefore they are not available in most companies, which is why it is an excellent option to generate these tools virtually.

One of the main technological trends, highlighted in recent years by various consultants, is the creation of digital twins, a concept that is sometimes also referred to by its name in English: 'Digital twins'. That it is a virtual replica of a product in this case that of a collaborative robot (cobot), this medium-sized robotic arm is easy to program, fast to configure and, with fast amortization times, it simulates the behaviour of its counterpart physical, with the aim of monitoring it, analysing its reaction to certain situations and problems and thus improving its performance and efficiency. Likewise, it combines digital and operational data from industrial resources with a software, simulation and analysis platform to obtain information on present and future operations. The result is improved production, reduced costs, accelerated innovation, and ultimately a solution that is much more than a product – it is the result the industry demands. Therefore, the implementation of a digital twin is specified in a real system or object whose structure and the information it handles have a virtual copy where it is possible to experiment safely and in an innovative way and in real time through reality. increased, which is very beneficial for manufacturing processes and to improve performance, reduce downtime and speed up the development of new products.

This chapter presents an extension of a research work (Rodríguez et al., 2021), that is about how to manipulate the virtual twin of a 6 Degree of Freedom (DOF) collaborative robot (cobot) using a platform developed in Unity under the augmented reality technique and to present and discuss several possible applications. In practice a robot is a mechatronic system, for this application, it is necessary to consider that a robot is a virtual entity, that by its appearance and its movements reproduces that behaviour of a real one. The chapter is organized in the following sections: Introduction, background, methodology; Section “Robot direct and inverse kinematics” presents the procedure to deduct the direct and inverse kinematics; “Implementing robot kinematics in unity” section, describes the implementation in Unity; “Physical and virtual robot communication” section contains the detailed description of the various phases that were passed through to manage to manipulate the robot virtually. “Robot operation space” section explains how the robot work area was delimited in both unity and TMflow® and, conclusions section.