Collaborative robots are becoming part of intelligent automation systems in modern industry. Development and control of such systems differs from traditional automation methods and consequently leads to new challenges. Thankfully, Robot Operating System (ROS) provides a communication platform and a vast variety of tools and utilities that can aid that development. However, it is hard to use ROS in large-scale automation systems due to communication issues in a distributed setup, hence the development of ROS2. In this paper, a ROS2 based communication architecture is presented together with an industrial use-case of a collaborative and intelligent automation system.Since the incarnation of ROS in 2007 [3] by Willow Garage, the number of ROS users has seen a major increase with more than 16 million total downloads in the year 2018 [4]. Currently, ROS2 [5] is being developed, where the communication layer is based on Data Distribution Service (DDS) [6] to enable large scale distributed control architectures. As it is presented in this paper, this improvement paves the way for use of ROS2-based architectures in real-world industrial automation systems.Since ROS2 is behind ROS when it comes to the number of packages and active developers, communication bridges are used to pass messages between ROS and ROS2. These bridges allow the community to utilize strengths of both ROS and ROS2 in the same system, i.e. to have an extensive set of developed packages and at the same time have a robust way to communicate between machines. This is crucial in modern industry because it enables robust integration of state-of-the-art tools and algorithms necessary for control in collaborative and intelligent automation systems. Since these large-scale automation systems are usually distributed in nature, they require a well structured and reliable communication architecture. Therefore, this paper presents variations of a ROS2 based communication architecture with these traits.While enabling integration and communication is greatly beneficial, it is just one part of the challenge. The overall control architecture also needs to plan and coordinate all actions of robots, humans and other devices as well as to keep track of everything. Mixed human-machine industrial environments where operations are carried out either collaboratively, coactively or individually, demand non-traditional control strategies. A few ROS based frameworks that try to handle these control strategies are ROSPlan [7], SkiROS [8], eTaSL/eTC [9] and CoSTAR [10]. These frameworks are however mainly focused on single robot systems and as such lack the infrastructure to support large scale automation systems. Intelligent and collaborative systems often comprise of several robots, machines, smart tools, human-machine interfaces, cameras, safety sensors, etc.A use-case in this paper illustrates the challenges of achieving flexible automation in an industrial setup and highlights the need to use ROS due to great integration with smart devices and algorithms. A brief overview ...

In order to adapt to stricter system delivery and integration requirements, virtual commissioning (VC) has become a well adopted practice in industry. VC is getting increasingly integrated into the overall engineering process, where the control software is continuously tested with the virtual plant model. At the same time, collaborative and intelligent automation systems are becoming an important part of modern industries. In these complex systems, humans perform operations together with collaborative robots, intelligent machines and smart tools. However, performing VC of such complex, distributed and heterogeneous systems demands new ways of interfacing different hardware and software components. This paper discusses the requirements, process and results of integrated virtual commissioning of an industrial collaborative and intelligent automation system usecase. Moreover, this industrial use-case illustrates challenges and exemplifies the need to use the next generation Robot Operating System (ROS2) due to its robust communication layer as well as easy integration with smart devices and algorithms.

Collaborative and intelligent automation systems need intelligent control systems. Some of this intelligence exist on a per-component basis in the form of vision, sensing, motion, and path planning algorithms. To fully take advantage of this intelligence, also the coordination of subsystems need to exhibit intelligence. While there exist middleware solutions that eases communication, development, and reuse of such subsystems, for example the Robot Operating System (ROS), good coordination also requires knowledge about how control is supposed to be performed, as well as expected behavior of the subsystems. This paper introduces lightweight components that wraps ROS2 nodes into composable control components from which an intelligent control system can be built. The ideas are implemented on a use case involving collaborative robots with on-line path planning, intelligent tools, and human operators.

In many modern automation solutions, manual off-line programming is being replaced by online algorithms that dynamically perform tasks based on the state of the environment. Complexities of such systems are pushed even further with collaboration among robots and humans, where intelligent machines and learning algorithms are replacing more traditional automation solutions. This chapter describes the development of an industrial demonstrator using a control infrastructure called Sequence Planner (SP), and presents some lessons learned during development. SP is based on ROS2 and it is designed to aid in handling the increased complexity of these new systems using formal models and online planning algorithms to coordinate the actions of robots and other devices. During development, SP can auto generate ROS nodes and message types as well as support continuous validation and testing. SP is also designed with the aim to handle traditional challenges of automation software development such as safety, reliability and efficiency. In this chapter, it is argued that ROS2 together with SP could be an enabler of intelligent automation for the next industrial revolution.

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