A Hybrid Model for Situation Monitoring and Conflict Prediction in Human Supervised “Autonomous” Systems

The paper focuses on a key issue for human supervised “autonomous” systems, namely situation monitoring. The operator’s involvement within human-robot team is first described as the way they close the control and decision loops. Then a framework based on particle filtering and Petri nets is presented for hybrid numerical-symbolic situation monitoring and inconsistency and conflict prediction within the team.