Avoiding the state explosion problem in temporal logic model checking
PODC '87 Proceedings of the sixth annual ACM Symposium on Principles of distributed computing
UPPAAL—a tool suite for automatic verification of real-time systems
Proceedings of the DIMACS/SYCON workshop on Hybrid systems III : verification and control: verification and control
On the temporal analysis of fairness
POPL '80 Proceedings of the 7th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Design and Control of Autonomous Underwater Robots: A Survey
Autonomous Robots
Using Situated Communication in Distributed Autonomous Mobile Robotics
SCAI '01 Proceedings of the Seventh Scandinavian Conference on Artificial Intelligence
NuSMV 2: An OpenSource Tool for Symbolic Model Checking
CAV '02 Proceedings of the 14th International Conference on Computer Aided Verification
Design and Synthesis of Synchronization Skeletons Using Branching-Time Temporal Logic
Logic of Programs, Workshop
ASE '00 Proceedings of the 15th IEEE international conference on Automated software engineering
Counterexample-guided abstraction refinement for symbolic model checking
Journal of the ACM (JACM)
Verification of NASA Emergent Systems
ICECCS '04 Proceedings of the Ninth IEEE International Conference on Engineering Complex Computer Systems Navigating Complexity in the e-Engineering Age
Distributed, Physics-Based Control of Swarms of Vehicles
Autonomous Robots
Symmetry in temporal logic model checking
ACM Computing Surveys (CSUR)
Counterexample-guided predicate abstraction of hybrid systems
Theoretical Computer Science - Tools and algorithms for the construction and analysis of systems (TACAS 2003)
Principles of Model Checking (Representation and Mind Series)
Principles of Model Checking (Representation and Mind Series)
Spin model checker, the: primer and reference manual
Spin model checker, the: primer and reference manual
Fair Derivations in Monodic Temporal Reasoning
CADE-22 Proceedings of the 22nd International Conference on Automated Deduction
Strategies for energy optimisation in a swarm of foraging robots
SAB'06 Proceedings of the 2nd international conference on Swarm robotics
Modeling and Optimization of Adaptive Foraging in Swarm Robotic Systems
International Journal of Robotics Research
An Introduction to Practical Formal Methods Using Temporal Logic
An Introduction to Practical Formal Methods Using Temporal Logic
Towards temporal verification of emergent behaviours in swarm robotic systems
TAROS'11 Proceedings of the 12th Annual conference on Towards autonomous robotic systems
Analysing robot swarm behaviour via probabilistic model checking
Robotics and Autonomous Systems
From swarm intelligence to swarm robotics
SAB'04 Proceedings of the 2004 international conference on Swarm Robotics
PRISM: a tool for automatic verification of probabilistic systems
TACAS'06 Proceedings of the 12th international conference on Tools and Algorithms for the Construction and Analysis of Systems
Temporal Logic Planning and Control of Robotic Swarms by Hierarchical Abstractions
IEEE Transactions on Robotics
Robotics and Autonomous Systems
Hi-index | 0.00 |
A robot swarm is a collection of simple robots designed to work together to carry out some task. Such swarms rely on the simplicity of the individual robots; the fault tolerance inherent in having a large population of identical robots; and the self-organised behaviour of the swarm as a whole. Although robot swarms present an attractive solution to demanding real-world applications, designing individual control algorithms that can guarantee the required global behaviour is a difficult problem. In this paper we assess and apply the use of formal verification techniques for analysing the emergent behaviours of robotic swarms. These techniques, based on the automated analysis of systems using temporal logics, allow us to analyse whether all possible behaviours within the robot swarm conform to some required specification. In particular, we apply model-checking, an automated and exhaustive algorithmic technique, to check whether temporal properties are satisfied on all the possible behaviours of the system. We target a particular swarm control algorithm that has been tested in real robotic swarms, and show how automated temporal analysis can help to refine and analyse such an algorithm.