Kernel Design and Distributed, Self-Triggered Control for Coordination of Autonomous Multi-Agent Configurations
| Autor: | Aaron Sims, Levi DeVries, Michael D. M. Kutzer |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Graph rewriting Computer science General Mathematics Distributed computing 020208 electrical & electronic engineering Kernel design 02 engineering and technology Experimental validation Computer Science Applications 020901 industrial engineering & automation Control and Systems Engineering 0202 electrical engineering electronic engineering information engineering Graph (abstract data type) Topological graph theory Cloud server Laplace operator Implementation Software |
| Zdroj: | Robotica. 36:1077-1097 |
| ISSN: | 1469-8668 0263-5747 |
| DOI: | 10.1017/s0263574718000231 |
| Popis: | SUMMARYAutonomous multi-agent systems show promise in countless applications, but can be hindered in environments where inter-agent communication is limited. In such cases, this paper considers a scenario where agents communicate intermittently through a cloud server. We derive a graph transformation mapping the kernel of a graph's Laplacian to a desired configuration vector while retaining graph topology characteristics. The transformation facilitates derivation of a self-triggered controller driving agents to prescribed configurations while regulating instances of inter-agent communication. Experimental validation of the theoretical results shows the self-triggered approach drives agents to a desired configuration using fewer control updates than traditional periodic implementations. |
| Databáze: | OpenAIRE |
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