Multi-objective control problems for multi-robot systems in constrained environments: A set-theoretic formulation
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The development of planning, coordination and control algorithms for complex systems, such as robotic networks and multi-vehicle systems under multiple tasks, is nowadays motivated by numerous applications. Networked autonomous vehicles, such as aerial, space, marine and ground robots are typically of non-trivial dynamics, often deployed in uncertain environments and also of restricted sensing and communication capabilities. Requirements such as safety of the individual components and reliability of the overall networked system give rise to control objectives which include inter-agent collision avoidance, connectivity maintenance among agents and effective coverage of the environment. In this talk we will present control design methodologies for systems subject to motion and state constraints, which encode sensing and communication restrictions. The methodology relies on a novel class of Lyapunov-like barrier functions, which give rise to a set-theoretic formulation amenable to distributed control design with Lyapunov-like techniques. Our recent results address the safe coordination and dynamic coverage for multi-robot systems in obstacle environments under sensing and communication constraints.