Survey on safe robot control via learning
It addresses the problem of ensuring safety in robot control for industries like aerospace and healthcare, but it is incremental as it reviews existing literature without presenting new results.
This survey investigates methods for balancing high-performance control with rigorous safety constraints in robotic systems, aiming to prevent hazardous states while maintaining optimal performance across complex environments.
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.