Control systems are critical to modern technological infrastructure, spanning industries from aerospace to healthcare. This survey explores the landscape of safe robot learning, investigating methods that balance high-performance control with rigorous safety constraints. By examining classical control techniques, learning-based approaches, and embedded system design, the research seeks to understand how robotic systems can be developed to prevent hazardous states while maintaining optimal performance across complex operational environments.
@article{arxiv.2501.01432,
title = {Survey on safe robot control via learning},
author = {Bassel El Mabsout},
journal= {arXiv preprint arXiv:2501.01432},
year = {2025}
}