Formation control algorithms for multi-agent systems have gained much attention in the recent years due to the increasing amount of mobile and aerial robotic swarms. The design of safe controllers for these vehicles is a substantial aspect for an increasing range of application domains. However, parts of the vehicle's dynamics and external disturbances are often unknown or very time-consuming to model. To overcome this issue, we present a safe formation control law for multiagent systems based on double integrator dynamics by using Gaussian Processes for an online learning of the unknown dynamics. The presented approach guarantees a bounded error to desired formations with high probability, where the bound is explicitly given. A numerical example highlights the effectiveness of the learning-based formation control law.
@article{arxiv.2104.00130,
title = {Safe Online Learning-based Formation Control of Multi-Agent Systems with Gaussian Processes},
author = {Thomas Beckers and Sandra Hirche and Leonardo Colombo},
journal= {arXiv preprint arXiv:2104.00130},
year = {2021}
}