The emergence of the Internet of things and the widespread deployment of diverse computing systems have led to the formation of heterogeneous multi-agent systems (MAS) to complete a variety of tasks. Motivated to highlight the state of the art on existing MAS while identifying their limitations, remaining challenges, and possible future directions, we survey recent contributions to the field. We focus on robot agents and emphasize the challenges of MAS sub-fields including task decomposition, coalition formation, task allocation, perception, and multi-agent planning and control. While some components have seen more advancements than others, more research is required before effective autonomous MAS can be deployed in real smart city settings that are less restrictive than the assumed validation environments of MAS. Specifically, more autonomous end-to-end solutions need to be experimentally tested and developed while incorporating natural language ontology and dictionaries to automate complex task decomposition and leveraging big data advancements to improve perception algorithms for robotics.

Cooperative Heterogeneous Multi-Robot Systems: A Survey

Autonomous robotic systems are complex, hybrid, and often safety critical; this makes their formal specification and verification uniquely challenging. Though commonly used, testing and simulation alone are insufficient to ensure the correctness of, or provide sufficient evidence for the certification of, autonomous robotics. Formal methods for autonomous robotics have received some attention in the literature, but no resource provides a current overview. This article systematically surveys the state of the art in formal specification and verification for autonomous robotics. Specially, it identifies and categorizes the challenges posed by, the formalisms aimed at, and the formal approaches for the specification and verification of autonomous robotics.

https://dl.acm.org/doi/pdf/10.1145/3342355

Formal Specification and Verification of Autonomous Robotic Systems: A Survey

Autonomous robotic systems are complex, hybrid, and often safety-critical; this makes their formal specification and verification uniquely challenging. Though commonly used, testing and simulation alone are insufficient to ensure the correctness of, or provide sufficient evidence for the certification of, autonomous robotics. Formal methods for autonomous robotics has received some attention in the literature, but no resource provides a current overview. This paper systematically surveys the state-of-the-art in formal specification and verification for autonomous robotics. Specially, it identifies and categorises the challenges posed by, the formalisms aimed at, and the formal approaches for the specification and verification of autonomous robotics.

Robots are becoming ubiquitous: from vacuum cleaners to driverless cars, there is a wide variety of applications, many with potential safety hazards. The work presented in this paper proposes a set of constructs suitable for both modelling robotic applications and supporting verification via model checking and theorem proving. Our goal is to support roboticists in writing models and applying modern verification techniques using a language familiar to them. To that end, we present RoboChart, a domain-specific modelling language based on UML, but with a restricted set of constructs to enable a simplified semantics and automated reasoning. We present the RoboChart metamodel, its well-formedness rules, and its process-algebraic semantics. We discuss verification based on these foundations using an implementation of RoboChart and its semantics as a set of Eclipse plug-ins called RoboTool.

/pdf/robochart-modelling-and-verification-of-the-functional-y1flbnqo7p.pdf

RoboChart: modelling and verification of the functional behaviour of robotic applications

The last five years marked a surge in interest for and use of smart robots, which operate in dynamic and unstructured environments and might interact with humans. We posit that well-validated computer simulation can provide a virtual proving ground that in many cases is instrumental in understanding safely, faster, at lower costs, and more thoroughly how the robots of the future should be designed and controlled for safe operation and improved performance. Against this backdrop, we discuss how simulation can help in robotics, barriers that currently prevent its broad adoption, and potential steps that can eliminate some of these barriers. The points and recommendations made concern the following simulation-in-robotics aspects: simulation of the dynamics of the robot; simulation of the virtual world; simulation of the sensing of this virtual world; simulation of the interaction between the human and the robot; and, in less depth, simulation of the communication between robots. This Perspectives contribution summarizes the points of view that coalesced during a 2018 National Science Foundation/Department of Defense/National Institute for Standards and Technology workshop dedicated to the topic at hand. The meeting brought together participants from a range of organizations, disciplines, and application fields, with expertise at the intersection of robotics, machine learning, and physics-based simulation.

https://www.pnas.org/content/pnas/118/1/e1907856118.full.pdf

On the use of simulation in robotics: Opportunities, challenges, and suggestions for moving forward.

Robotic systems are multi-dimensional entities, combining both hardware and software, that are heavily dependent on, and influenced by, interactions with the real world. They can be variously categorised as embedded, cyber-physical, real-time, hybrid, adaptive and even autonomous systems, with a typical robotic system being likely to contain all of these aspects. The techniques for developing and verifying each of these system varieties are often quite distinct. This, together with the sheer complexity of robotic systems, leads us to argue that diverse formal techniques must be integrated in order to develop, verify, and provide certification evidence for, robotic systems. Furthermore, we propose the fast evolving field of robotics as an ideal catalyst for the advancement of integrated formal methods research, helping to drive the field in new and exciting directions and shedding light on the development of large-scale, dynamic, complex systems.

Robotics and Integrated Formal Methods: Necessity Meets Opportunity

Robotic systems are multi-dimensional entities, combining both hardware and software, that are heavily dependent on, and influenced by, interactions with the real world. They can be variously categorised as embedded, cyberphysical, real-time, hybrid, adaptive and even autonomous systems, with a typical robotic system being likely to contain all of these aspects. The techniques for developing and verifying each of these system varieties are often quite distinct. This, together with the sheer complexity of robotic systems, leads us to argue that diverse formal techniques must be integrated in order to develop, verify, and provide certification evidence for, robotic systems. Furthermore, we propose the fast evolving field of robotics as an ideal catalyst for the advancement of integrated formal methods research, helping to drive the field in new and exciting directions and shedding light on the development of large-scale, dynamic, complex systems.

Marie Farrell

Papers

Formal Specification and Verification of Autonomous Robotic Systems: A Survey

Formal Specification and Verification of Autonomous Robotic Systems: A Survey

Robotics and Integrated Formal Methods: Necessity Meets Opportunity

Robotics and Integrated Formal Methods: Necessity meets Opportunity

An Overview of Verification and Validation Challenges for Inspection Robots