Perception Contract

Perception contracts are a formal framework for verifying the safety of autonomous systems that rely on machine learning for perception, aiming to guarantee reliable operation despite inherent uncertainties in sensor data. Current research focuses on developing methods to automatically learn and refine these contracts from data, often employing inverse perception contracts to characterize perception errors and incorporate them into control algorithms. This approach is being applied to various systems, including autonomous vehicles and drone swarms, improving safety and reliability in challenging environments where traditional methods fall short. The resulting advancements have significant implications for the safety and deployment of increasingly complex autonomous systems.