Towards Robust Autonomous Robots Using Statistical Model Checking
摘要
Robots deployed outside controlled environments, often fail to take appropriate actions and require human intervention when facing unexpected situations. Our goal is to advance the capabilities of robots to perform complex tasks robustly within unstructured environments by validating their behavior using statistical model checking on the entire system. We discuss requirements to a common modeling language from two use cases and present first ideas for making model checking accessible for robotic system validation.