37 research outputs found
Formal methods for the design and analysis of robot swarms
In my doctoral dissertation, I tackled two of the main open problems in swarm robotics: design and verification. I did so by using model checking.Designing and developing individual-level behaviors to obtain a desired swarm-level goal is, in general, very difficult, as it is difficult to predict and thus design the non-linear interactions of tens or hundreds individual robots that result in the desired collective behavior. In my dissertation, I presented my novel contribution to the top-down design of robot swarms: property-driven design. Property-driven design is based on prescriptive modeling and model checking. Using property-driven design it is possible to design robot swarms in a systematic way, realizing systems that are "correct by design". I demonstrated property-driven design on two case-studies: aggregation and foraging.Developing techniques to analyze and verify a robot swarm is also a necessary step in order to employ swarm robotics in real-world applications. In my dissertation, I explored the use of model checking to analyze and verify the properties of robot swarms. Model checking allows us to formally describe a set of desired properties of a system, in a more powerful and precise way compared to other mathematical approaches, and verify whether a given model of a system satisfies them. I explored two different approaches: the first based on Bio-PEPA and the second based on KLAIM.Doctorat en Sciences de l'ingénieurinfo:eu-repo/semantics/nonPublishe
Property-driven design for robot swarms: A design method based on prescriptive modeling and model checking
In this article, we present property-driven design, a novel top-down design method for robot swarms based on prescriptive modeling and model checking. Traditionally, robot swarms have been developed using a codeand-fix approach: in a bottom-up iterative process, the developer tests and improves the individual behaviors of the robots until the desired collective behavior is obtained. The code-and-fix approach is unstructured, and the quality of the obtained swarm depends completely on the expertise and ingenuity of the developer who has little scientific or technical support in his activity. Property-driven design aims at providing such scientific and technical support, with many advantages compared to the traditional unstructured approach. Property-driven design is composed of four phases: first, the developer formally specifies the requirements of the robot swarm by stating its desired properties; second, the developer creates a prescriptive model of the swarm and uses model checking to verify that this prescriptive model satisfies the desired properties; third, using the prescriptive model as a blueprint, the developer implements a simulated version of the desired robot swarm and validates the prescriptive model developed in the previous step; fourth, the developer implements the desired robot swarm and validates the previous steps. We demonstrate property-driven design using two case studies: aggregation and foraging.SCOPUS: ar.jinfo:eu-repo/semantics/publishe
"Look out!": Socially-Mediated Obstacle Avoidance in Collective Transport
In collective transport, a group of robots has to cooperate in order to transport an object. Collective transport is necessary when transporting the object is hard or impossible for a single robot. The task is particularly difficult when communication bandwidth is limited, there is no access to global information or when using a decentralized approach. In these cases, an effective distributed coordination among the robots is necessary. © 2010 Springer-Verlag Berlin Heidelberg.Swarm Intelligence: 7th International Conference, ANTS 2010 (Brussels, Belgium, September 8-10, 2010)SCOPUS: cp.kinfo:eu-repo/semantics/publishe
A Reliable Distributed Algorithm for Group Size Estimation with Minimal Communication Requirements
Paper ID 137 CDinfo:eu-repo/semantics/publishe