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This work discusses the ongoing development of a toolset named MARS aimed to ease the process of safely deploying runtime verification monitors into distributed micro-ROS and ROS2 nodes. The work is motivated by a use case in the health and automotive domains and covers safety/security concerns around the manipulation of sensitive biometric data.This work was partially supported by National Funds through FCT/MCTES (Portuguese Foundation for Science and Technology), within the CISTER Research Unit (UIDP/UIDB/04234/2020); also by FCT within project ECSEL/0016/2019 and from the ECSEL Joint Undertaking (JU) under grant agreement No 876852. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Austria, Czech Republic, Germany, Ireland, Italy, Portugal, Spain, Sweden, Turkey. We would also like to thank Antonio Rodriguez and Pablo Garrido from eProsima for their collaboration in development of the secure custom transport layer of MARS. Disclaimer: This document reflects only the author’s view and the Commission is not responsible for any use that may be made of the information it contains)info:eu-repo/semantics/publishedVersio

Control components for Collaborative and Intelligent Automation Systems

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

Development of an Industry 4.0 Demonstrator Using Sequence Planner and ROS2

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

SROS2: Usable Cyber Security Tools for ROS 2

ROS 2 is rapidly becoming a standard in the robotics industry. Built upon DDS as its default communication middleware and used in safety-critical scenarios, adding security to robots and ROS computational graphs is increasingly becoming a concern. The present work introduces SROS2, a series of developer tools and libraries that facilitate adding security to ROS 2 graphs. Focusing on a usability-centric approach in SROS2, we present a methodology for securing graphs systematically while following the DevSecOps model. We also demonstrate the use of our security tools by presenting an application case study that considers securing a graph using the popular Navigation2 and SLAM Toolbox stacks applied in a TurtleBot3 robot. We analyse the current capabilities of SROS2 and discuss the shortcomings, which provides insights for future contributions and extensions. Ultimately, we present SROS2 as usable security tools for ROS 2 and argue that without usability, security in robotics will be greatly impaired.Comment: Accepted, IROS 2022, 7 pages, 2 figures, 5 code listings, 5 sections plus reference

SROS2: Usable Cyber Security Tools for ROS 2

ROS 2 is rapidly becoming a standard in the robotics industry. Built upon DDS as its default communication middleware and used in safety-critical scenarios, adding security to robots and ROS computational graphs is increasingly becoming a concern. The present work introduces SROS2, a series of developer tools and libraries that facilitate adding security to ROS 2 graphs. Focusing on a usability-centric approach in SROS2, we present a methodology for securing graphs systematically while following the DevSecOps model. We also demonstrate the use of our security tools by presenting an application case study that considers securing a graph using the popular Navigation2 and SLAM Toolbox stacks applied in a TurtleBot3 robot. We analyse the current capabilities of SROS2 and discuss the shortcomings, which provides insights for future contributions and extensions. Ultimately, we present SROS2 as usable security tools for ROS 2 and argue that without usability, security in robotics will be greatly impaired

Cyber Security Assessment of the Robot Operating System 2 for Aerial Networks

Best Student Paper, 2nd PlaceThe article of record as published may be found at https://doi.org/10.1109/SYSCON.2019.88368242019 IEEE International Systems Communications Conference (SYSCON)The Robot Operating System (ROS) is a widely adopted standard robotic middleware. However, its preliminary design is devoid of any network security features. Military grade unmanned systems must be guarded against network threats. ROS 2 is built upon the Data Distribution Service (DDS) standard and is designed to provide solutions to identified ROS 1 security vulnerabilities by incorporating authentication, encryption, and process profile features, which rely on public key infrastructure. The Department of Defense is looking to use ROS 2 for its military-centric robotics platform. This paper seeks to demonstrate that ROS 2 and its DDS security architecture can serve as a functional platform for use in military grade unmanned systems, particularly in unmanned Naval aerial swarms. In this paper, we focus on the viability of ROS 2 to safeguard communications between swarms and a ground control station (GCS). We test ROS 2’s ability to mitigate and withstand certain cyber threats, specifically that of rogue nodes injecting unauthorized data and accessing services that will disable parts of the UAV swarm. We use the Gazebo robotics simulator to target individual UAVs to ascertain the effectiveness of our attack vectors under specific conditions. We demonstrate the effectiveness of ROS 2 in mitigating the chosen attack vectors but observed a measurable operational delay within our simulations.This work was funded and sponsored by the Office of Naval Research via the Consortium for Robotics and Unmanned Systems Education and Research (CRUSER) at NPS

Procedurally Provisioned Access Control for Robotic Systems

Security of robotics systems, as well as of the related middleware infrastructures, is a critical issue for industrial and domestic IoT, and it needs to be continuously assessed throughout the whole development lifecycle. The next generation open source robotic software stack, ROS2, is now targeting support for Secure DDS, providing the community with valuable tools for secure real world robotic deployments. In this work, we introduce a framework for procedural provisioning access control policies for robotic software, as well as for verifying the compliance of generated transport artifacts and decision point implementations

Towards an infrastructure for preparation and control of intelligent automation systems

In an attempt to handle some of the challenges of modern production, intelligent automation systems offer solutions that are flexible, adaptive, and collaborative. Contrary to traditional solutions, intelligent automation systems emerged just recently and thus lack the supporting tools and infrastructure that traditional systems nowadays take for granted. To support efficient development, commissioning, and control of such systems, this thesis summarizes various lessons learned during years of implementation. Based on what was learned, this thesis investigates key features of infrastructure for modern and flexible intelligent automation systems, as well as a number of important design solutions. For example, an important question is raised whether to decentralize the global state or to give complete access to the main controller.Moreover, in order to develop such systems, a framework for virtual preparation and commissioning is presented, with the main goal to offer support for engineers. As traditional virtual commissioning solutions are not intended for preparing highly flexible, collaborative, and dynamic systems, this framework aims to provide some of the groundwork and point to a direction for fast and integrated preparation and virtual commissioning of such systems.Finally, this thesis summarizes some of the investigations made on planning as satisfiability, in order to evaluate how different methods improve planning performance. Throughout the thesis, an industrial material kitting use case exemplifies presented perspectives, lessons learned, and frameworks

Preparation and control of intelligent automation systems

In the automation systems of tomorrow, it is likely that the devices included have various degrees of autonomy, and include advanced algorithms for perception and control. Human operators will be expected to work together with collaborative robots as well as with roaming robots for material handling.The volatile nature of the environment of such intelligent automation systems lead to an enormous amount of possible situations that can arise and which need to be suitably handled. This complexity makes development of control systems for intelligent automation systems difficult using traditional methods.As an alternative, this thesis presents a model-based control framework, which uses a combination of formal specification and automated planning. The proposed framework allows for defining the intentions of the automation system on a high level, which enables decisions that influence when things should occur to be modeled using logical constraints, rather than programming. To achieve a modular framework, low level, reusable, resource models are composed by 1) formal specification to ensure safety and 2) applying an abstraction called an operation, which couples the reusable resources to the intentions of the system. By planning also the resources\u27 detailed actions, the operations can, when possible, be completed regardless of the resources\u27 current state. This eases error-recovery, as resources do not have to be reset when an error occurs.Additionally, the thesis proposes an iterative and interactive workflow for integrating the proposed model-based control framework into a virtual preparation process, using computer-based simulation as a tool for validating formal specifications. The control framework allows for adding new constraints to a running system, enabling an efficient and interactive preparation process.The framework has been applied to a use case from final assembly, which features human-robot collaboration. Experimental results on the ability to handle unforeseen errors and planning performance are presented