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Published on: January 19, 2019
Agent swarms: Cooperation and coordination under stringent communications constraint.
Paul Kinsler1, Sean Holman2, Andrew Elliott3
1Department of Electronic & Electrical Engineering University of Bath, Bath, United Kingdom.
This study introduces a novel model for agent swarms to connect in challenging communication environments. It focuses on agent-centric metrics and communication constraints for autonomous systems like drones and satellites.
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Area of Science:
- Robotics and Autonomous Systems
- Network Communications
- Distributed Systems
Background:
- Swarms of autonomous agents (satellites, drones) are crucial for exploration.
- Challenging communication environments pose significant hurdles for swarm connectivity.
- Constraints like stealth, power, and hardware limitations necessitate new communication strategies.
Purpose of the Study:
- To present a novel, discrete, geometry-free model for multi-agent swarm communications.
- To develop agent-centric performance metrics for swarms without global location knowledge.
- To analyze connectivity tactics under stringent communication constraints.
Main Methods:
- Developed a discrete, geometry-free communication model for agent swarms.
- Proposed agent-centric performance metrics to address lack of global knowledge.
- Simulated various connectivity tactics to evaluate outcomes, risks, and connectivity.
Main Results:
- Demonstrated how communication constraints dominate algorithmic outcomes in swarm connectivity.
- Showcased the impact of the information gain to information loss ratio on simulated outcomes.
- Identified excessive round-trip-time checks as an effective filtering mechanism.
Conclusions:
- The proposed framework enables testing of efficient communication tactics for agent swarms.
- The model is applicable to diverse scenarios and future autonomous systems.
- Agent-centric metrics and constraint-aware algorithms are vital for swarm communication success.