1 research outputs found
Model-Driven Requirements for Humans-on-the-Loop Multi-UAV Missions
The use of semi-autonomous Unmanned Aerial Vehicles (UAVs or drones) to
support emergency response scenarios, such as fire surveillance and
search-and-rescue, has the potential for huge societal benefits. Onboard
sensors and artificial intelligence (AI) allow these UAVs to operate
autonomously in the environment. However, human intelligence and domain
expertise are crucial in planning and guiding UAVs to accomplish the mission.
Therefore, humans and multiple UAVs need to collaborate as a team to conduct a
time-critical mission successfully. We propose a meta-model to describe
interactions among the human operators and the autonomous swarm of UAVs. The
meta-model also provides a language to describe the roles of UAVs and humans
and the autonomous decisions. We complement the meta-model with a template of
requirements elicitation questions to derive models for specific missions. We
also identify common scenarios where humans should collaborate with UAVs to
augment the autonomy of the UAVs. We introduce the meta-model and the
requirements elicitation process with examples drawn from a search-and-rescue
mission in which multiple UAVs collaborate with humans to respond to the
emergency. We then apply it to a second scenario in which UAVs support first
responders in fighting a structural fire. Our results show that the meta-model
and the template of questions support the modeling of the human-on-the-loop
human interactions for these complex missions, suggesting that it is a useful
tool for modeling the human-on-the-loop interactions for multi-UAVs missions.Comment: 10 page