| Abstract: |
| In this talk we focus on path-planning of Unmanned Aerial Vehicles (UAVs). These small versatile vehicles have proved to be a major asset in the increasingly demand for complex autonomous robotics missions. Our focus is on developing for a fleet of UAVs the ability to autonomously make decisions based on shared information. We use graph theory to produce an algorithm for a multi-agents system and apply it to UAVs detection and survey missions involving consensus, formation, coverage and swarming. In particular, agreement is one of the fundamental problems in multi-agents coordination, where a collection of agents are to agree on a joint state value. We assume the swarm to be fully distributed, without centralized control with communication and sensing usually local and minimal. Agents are identified as nodes of a network and edges are encoding the existence of their interaction. We will discuss the intricate relationship between the convergence properties of this protocol on one hand, and the structure of the underlying network connections on the other. |
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