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. Introduction, Methodology and Related WorkAn autonomous system is an artificially intelligent entity that makes decisions in response to input, independent of human interaction. Robotic systems are physical entities that interact with the physical world. Thus, we consider an autonomous robotic system as a machine that uses Artificial Intelligence (AI), has a physical presence in and interacts with the real world. They are complex, inherently hybrid, systems, combining both hardware and software; they often require close safety, legal, and ethical consideration. Autonomous robotics are increasingly being used in commonplace-scenarios, such as driverless cars [68], pilotless aircraft [176], and domestic assistants [174,60].While for many engineered systems, testing, either through real deployment or via simulation, is deemed sufficient; the unique challenges of autonomous robotics, their dependence on sophisticated software control and decision-making, and their increasing deployment in safety-critical scenarios, require a stronger form of verification. This leads us towards using formal methods, which are mathematically-based techniques for the specification and verification of software systems, to ensure the correctness of, and provide sufficient evidence for the certification of, robotic systems.We contribute an overview and analysis of the state-of-the-art in formal specification and verification of autonomous robotics. §1.1 outlines the scope, research questions and search criteria for our survey. §1.2 describes related work concerning formal methods for robotics and differentiates them from our work. We recognise the important role that middleware architectures and, non-and semi-formal techniques have in the development of reliable robotics and we briefly summarise some of these techniques in §2. The specification and verification challenges raised by autonomous robotic systems are discussed next: §3 describes the challenges of their context (the external challenges) and §4 describes the challenges of their organisation (the internal challenges). §5 discusses the formalisms used in the literature for specification and verification of autonomous robotics. §6 characterises the approaches to formal specification and verification of autonomous robotics found in the li...

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.

No abstract

The complexity and flexibility of autonomous robotic systems necessitates a range of distinct verification tools. This presents new challenges not only for design verification but also for assurance approaches. Combining the distinct formal verification tools, while maintaining sufficient formal coherence to provide compelling assurance evidence is difficult, often being abandoned for less formal approaches. In this paper we demonstrate, through a case study, how a variety of distinct formal techniques can be brought together in order to develop a justifiable assurance case. We use the AdvoCATE assurance case tool to guide our analyses and to integrate the artifacts from the formal methods that we use, namely: fret, cocosim and Event-B. While we present our methodology as applied to a specific Inspection Rover case study, we believe that this combination provides benefits in maintaining coherent formal links across development and assurance processes for a wide range of autonomous robotic systems.

The advent of sophisticated robotics and AI technology makes sending humans into hazardous and distant environments to carry out inspections increasingly avoidable. Being able to send a robot, rather than a human, into a nuclear facility or deep space is very appealing. However, building these robotic systems is just the start and we still need to carry out a range of verification and validation tasks to ensure that the systems to be deployed are as safe and reliable as possible. Based on our experience across three research and innovation hubs within the UK’s “Robots for a Safer World” programme, we present an overview of the relevant techniques and challenges in this area. As the hubs are active across nuclear, offshore, and space environments, this gives a breadth of issues common to many inspection robots.