Engineering Dynamic Risk and Capability Models to Improve Cooperation Efficiency Between Human Workers and Autonomous Mobile Robots in Shared Spaces

Coexistence or even cooperation of autonomous mobile robots (AMR) and humans is a key ingredient for future visions of production, warehousing and smart logistic. Before these visions can become reality one of the fundamental challenges to be tackled is safety assurance. Existing safety concepts have significant drawbacks, they either physically separate operation spaces completely or stop the AMR if its planned trajectory overlaps with a risk area constructed around a human worker based on a worst-case assumption. In the best case, this leads to only less-than-optimal performance, in the worst case an application idea might prove to be completely unfeasible. A general solution is to replace static worst-case assumptions with dynamic safety reasoning capabilities. This paper introduces a corresponding solution concept based on dynamic risk and capability models which enables safety assurance and at the same time allows for continuous optimization of performance properties.