Robotic Datasets for Process Mining

Flavio Corradini, Sara Pettinari, Barbara Re, Lorenzo Rossi, Massimiliano Sampaolo

Abstract: As robotic systems become increasingly integrated into real-world applications, the need to better understand their operations continues to grow. Bridging the gap between process mining and robotics can enhance the transparency, accountability, and efficiency of these systems. However, applying process mining in this context is challenging due to the nature of robotic event data, which is mainly fine-grained and composed of multi-sensor readings rather than high-level activity events. In this exploratory paper, we present a collection of publicly available robotic datasets, providing a valuable resource for researchers and practitioners aiming to apply process mining to robotic systems. We identify 118 datasets and classify them based on application domain, type of robot involved, onboard sensors, collaborative behaviors, and their readiness for processing with process mining techniques.