Plausibility verification for situation awareness in safe human-robot cooperation

Achieving seamless human-robot cooperation requires the robot to recognize its surroundings and be aware of human actions and their implications. Still, no recognition method, e.g., for objects or actions, can achieve zero failure rates. Thus, robotic actions might be selected and planned based on false assumptions. This inherits risks for humans and machinery. Consequently, the verification of plausibility of recognition results considered in context can extract inconsistencies and regulate robotic behavior due to adapted risk assessment. In this paper, an approach for plausibility verification in a situation awareness system and corresponding risk estimation adaptation is presented and examined.