Towards formal models and languages for verifiable Multi-Robot Systems

Incorrect operations of a Multi-Robot System (MRS) may not only lead to unsatisfactory results, but can also cause economic losses and threats to safety. These threats may not always be apparent, since they may arise as unforeseen consequences of the interactions between elements of the system. This call for tools and techniques that can help in providing guarantees about MRSs behaviour. We think that, whenever possible, these guarantees should be backed up by formal proofs to complement traditional approaches based on testing and simulation. We believe that tailored linguistic support to specify MRSs is a major step towards this goal. In particular, reducing the gap between typical features of an MRS and the level of abstraction of the linguistic primitives would simplify both the specification of these systems and the verification of their properties. In this work, we review different agent-oriented languages and their features; we then consider a selection of case studies of interest and implement them useing the surveyed languages. We also evaluate and compare effectiveness of the proposed solution, considering, in particular, easiness of expressing non-trivial behaviour.Comment: Changed formattin

Towards Verifiably Ethical Robot Behaviour

Ensuring that autonomous systems work ethically is both complex and difficult. However, the idea of having an additional `governor' that assesses options the system has, and prunes them to select the most ethical choices is well understood. Recent work has produced such a governor consisting of a `consequence engine' that assesses the likely future outcomes of actions then applies a Safety/Ethical logic to select actions. Although this is appealing, it is impossible to be certain that the most ethical options are actually taken. In this paper we extend and apply a well-known agent verification approach to our consequence engine, allowing us to verify the correctness of its ethical decision-making.Comment: Presented at the 1st International Workshop on AI and Ethics, Sunday 25th January 2015, Hill Country A, Hyatt Regency Austin. Will appear in the workshop proceedings published by AAA

On proactive, transparent and verifiable ethical reasoning for robots

Previous work on ethical machine reasoning has largely been theoretical, and where such systems have been implemented it has in general been only initial proofs of principle. Here we address the question of desirable attributes for such systems to improve their real world utility, and how controllers with these attributes might be implemented. We propose that ethically-critical machine reasoning should be proactive, transparent and verifiable. We describe an architecture where the ethical reasoning is handled by a separate layer, augmenting a typical layered control architecture, ethically moderating the robot actions. It makes use of a simulation-based internal model, and supports proactive, transparent and verifiable ethical reasoning. To do so the reasoning component of the ethical layer uses our Python based Beliefs, Desires, Intentions (BDI) implementation. The declarative logic structure of BDI facilitates both transparency, through logging of the reasoning cycle, and formal verification methods. To prove the principles of our approach we use a case study implementation to experimentally demonstrate its operation. Importantly, it is the first such robot controller where the ethical machine reasoning has been formally verified

Using Formal Methods for Autonomous Systems: Five Recipes for Formal Verification

Formal Methods are mathematically-based techniques for software design and engineering, which enable the unambiguous description of and reasoning about a system's behaviour. Autonomous systems use software to make decisions without human control, are often embedded in a robotic system, are often safety-critical, and are increasingly being introduced into everyday settings. Autonomous systems need robust development and verification methods, but formal methods practitioners are often asked: Why use Formal Methods for Autonomous Systems? To answer this question, this position paper describes five recipes for formally verifying aspects of an autonomous system, collected from the literature. The recipes are examples of how Formal Methods can be an effective tool for the development and verification of autonomous systems. During design, they enable unambiguous description of requirements; in development, formal specifications can be verified against requirements; software components may be synthesised from verified specifications; and behaviour can be monitored at runtime and compared to its original specification. Modern Formal Methods often include highly automated tool support, which enables exhaustive checking of a system's state space. This paper argues that Formal Methods are a powerful tool for the repertoire of development techniques for safe autonomous systems, alongside other robust software engineering techniques.Comment: Accepted at Journal of Risk and Reliabilit

Certified Impossibility Results for Byzantine-Tolerant Mobile Robots

We propose a framework to build formal developments for robot networks using the COQ proof assistant, to state and to prove formally various properties. We focus in this paper on impossibility proofs, as it is natural to take advantage of the COQ higher order calculus to reason about algorithms as abstract objects. We present in particular formal proofs of two impossibility results forconvergence of oblivious mobile robots if respectively more than one half and more than one third of the robots exhibit Byzantine failures, starting from the original theorems by Bouzid et al.. Thanks to our formalization, the corresponding COQ developments are quite compact. To our knowledge, these are the first certified (in the sense of formally proved) impossibility results for robot networks

Agents and Robots for Reliable Engineered Autonomy

This book contains the contributions of the Special Issue entitled "Agents and Robots for Reliable Engineered Autonomy". The Special Issue was based on the successful first edition of the "Workshop on Agents and Robots for reliable Engineered Autonomy" (AREA 2020), co-located with the 24th European Conference on Artificial Intelligence (ECAI 2020). The aim was to bring together researchers from autonomous agents, as well as software engineering and robotics communities, as combining knowledge from these three research areas may lead to innovative approaches that solve complex problems related to the verification and validation of autonomous robotic systems

A Roadmap to Pervasive Systems Verification

yesThe complexity of pervasive systems arises from the many different aspects that such systems possess. A typical pervasive system may be autonomous, distributed, concurrent and context-based, and may involve humans and robotic devices working together. If we wish to formally verify the behaviour of such systems, the formal methods for pervasive systems will surely also be complex. In this paper, we move towards being able to formally verify pervasive systems and outline our approach wherein we distinguish four distinct dimensions within pervasive system behaviour and utilise different, but appropriate, formal techniques for verifying each one.EPSR

Automated Reasoning and Robotics

A most important quality in robotics is the work done in the development of automated reasoning techniques. This model of reasoning works on the assistance of computer programs and just as it is in other fields, it has worked to aid in the answering of certain open questions. The aim of this survey is to study the applications of automated reasoning in the field of robotics and to evaluate its efficiency as a reasoning technique when applied. It is based generally on research into reasoning techniques applied to robotics and running an evaluation in contrast to automated reasoning to determine the rates of effectiveness between them. This process involves a basic understanding of how reasoning is implemented in relation to robotics, after which varying reasoning techniques and applications are discussed and compared in relation to automated reasoning and how automated reasoning would work to enhance results retrieved. The primary objective in this study is to identify the effectiveness of automated reasoning techniques to other techniques available and it begins with an introduction providing an overview of the concepts discussed before proceeding to examine the technicalities involved and which level of technicality is best