A formal approach to modeling self-adaptive behavior for swarm robotics

Best Paper ICTCC 2014

Two researchers from the Lero-the Irish Software Engineering Research Centre, University of Limerick, (Limerick, Ireland) presented a formal approach to modeling self-adaptive behavior of swarm robotics.

The study won the Best Paper award at the last year’s edition of the International Conference on Nature of Computation and Communication (ICTCC 2014) which took place on November 24–25, 2014 in Ho Chi Minh City, Vietnam.

Emil Vassev and Mike Hinchey presented an approach to capturing the requirements for, and modeling self-adaptive behavior, of swarm robotics. They used ‘KnowLang’: a formal framework under development under the mandate of the FP7 project, ASCENS. KnowLang’s notation is a formal language dedicated to knowledge representation for self-adaptive systems, so the framework provides both a notation and reasoning to deal with self-adaptation.

The research aimed to capture self-adaptive behavior so that it could be properly designed and subsequently implemented. To do so, it considered that self-adaptive behavior extends the regular objectives of a system upstream with special self-managing objectives, also called self-* objectives. The approach for capturing all of these requirements is called Autonomy Requirements Engineering (ARE). This approach aims to provide a complete and comprehensive solution to the problem of autonomy requirements elicitation and specification.

The ensemble of robots case study targets swarms of intelligent robots with selfawareness capabilities that help the entire swarm acquire the capacity to reason, plan, and autonomously act. The case study relies on the marXbot robotics platform, which is a modular research robot equipped with a set of devices that help the robot interact with other robots of the swarm or the robotic environment: an arena where special cuboid-shaped obstacles are present in arbitrary positions and orientations. Following this scenario, the researchers applied the ARE approach and derived the goals along with the self-* objectives assisting these goals when self-adaptation is required.

And finally, what are the expectations for the future? Future work is mainly concerned with further development of the Autonomy Requirements Engineering approach along with full implementation of KnowLang, involving tools and a test bed for autonomy requirements verification and validation.

To view and read the full paper you can click here.

Editorial Staff

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