# Coordination of multi-agent systems via asynchronous cloud communication

## TL;DR

This paper introduces a self-triggered multi-agent coordination algorithm that minimizes cloud communication by using promises about future control inputs, ensuring asymptotic convergence without continuous listening.

## Contribution

It presents a novel self-triggered control method for multi-agent systems that reduces communication by leveraging promises, without requiring agents to listen continuously.

## Key findings

- The algorithm guarantees asymptotic convergence to desired states.
- Agents can communicate less frequently while maintaining coordination.
- Simulations validate the effectiveness of the proposed approach.

## Abstract

In this work we study a multi-agent coordination problem in which agents are only able to communicate with each other intermittently through a cloud server. To reduce the amount of required communication, we develop a self-triggered algorithm that allows agents to communicate with the cloud only when necessary rather than at some fixed period. Unlike the vast majority of similar works that propose distributed event- and/or self-triggered control laws, this work doesn't assume agents can be "listening" continuously. In other words, when an event is triggered by one agent, neighboring agents will not be aware of this until the next time they establish communication with the cloud themselves. Using a notion of "promises" about future control inputs, agents are able to keep track of higher quality estimates about their neighbors allowing them to stay disconnected from the cloud for longer periods of time while still guaranteeing a positive contribution to the global task. We prove that our self-triggered coordination algorithm guarantees that the system asymptotically reaches the set of desired states. Simulations illustrate our results.