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1. Model-Driven Requirements for Humans-on-the-Loop Multi-UAV Missions

   https://doi.org/10.1109/MoDRE51215.2020.00007  

   Agrawal, Ankit; Cleland-Huang, Jane; Steghofer, Jan-Philipp (August 2020, Model-Driven Requirements Engineering)

   null (Ed.)

   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. 

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2. Area-Optimized UAV Swarm Network for Search and Rescue Operations

   https://doi.org/10.1109/CCWC47524.2020.9031197  

   Ruetten, Laik; Regis, Paulo Alexandre; Feil-Seifer, David; Sengupta, Shamik (January 2020, Computing and Communication Workshop and Conference (CCWC))

   null (Ed.)

   Intelligent robot swarms are increasingly being explored as tools for search and rescue missions. Efficient path planning and robust communication networks are critical elements of completing missions. The focus of this research is to give unmanned aerial vehicles (UAVs) the ability to self-organize a mesh network that is optimized for area coverage. The UAVs will be able to read the communication strength between themselves and all the UAVs it is connected to using RSSI. The UAVs should be able to adjust their positioning closer to other UAVs if RSSI is below a threshold, and they should also maintain communication as a group if they move together along a search path. Our approach was to use Genetic Algorithms in a simulated environment to achieve multi-node exploration with emphasis on connectivity and swarm spread. 

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3. The Next Generation of Human-Drone Partnerships: Co-Designing an Emergency Response System

   https://doi.org/10.1145/3313831.3376825  

   Agrawal, Ankit; Abraham, Sophia J.; Burger, Benjamin; Christine, Chichi; Fraser, Luke; Hoeksema, John M.; Hwang, Sarah; Travnik, Elizabeth; Kumar, Shreya; Scheirer, Walter; et al (April 2020, CHI Conference on Human Factors in Computing Systems)

   The use of semi-autonomous Unmanned Aerial Vehicles (UAV) to support emergency response scenarios, such as fire surveillance and search and rescue, offers the potential for huge societal benefits. However, designing an effective solution in this complex domain represents a ``wicked design'' problem, requiring a careful balance between trade-offs associated with drone autonomy versus human control, mission functionality versus safety, and the diverse needs of different stakeholders. This paper focuses on designing for situational awareness (SA) using a scenario-driven, participatory design process. We developed SA cards describing six common design-problems, known as SA demons, and three new demons of importance to our domain. We then used these SA cards to equip domain experts with SA knowledge so that they could more fully engage in the design process. We designed a potentially reusable solution for achieving SA in multi-stakeholder, multi-UAV, emergency response applications. 

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4. Aerial Border Surveillance for Search and Rescue Missions Using Eye Tracking Techniques

   https://doi.org/10.1109/THS.2018.8574165  

   Wan, Qianwen; Kaszowska, Aleksandra; Samani, Arash; Panetta, Karen; Taylor, Holly A.; Agaian, Sos (October 2018, 2018 IEEE International Symposium on Technologies for Homeland Security (HST))

   which can assure the security of the country boarder and aid in search and rescue missions. This paper offers a novel “handsfree” tool for aerial border surveillance, search and rescue missions using head-mounted eye tracking technology. The contributions of this work are: i) a gaze based aerial boarder surveillance object classification and recognition framework; ii) real-time object detection and identification system in nonscanned regions; iii) investigating the scan-path (fixation and non-scanned) provided by mobile eye tracker can help improve training professional search and rescue organizations or even artificial intelligence robots for searching and rescuing missions. The proposed system architecture is further demonstrated using a dataset of large-scale real-life head-mounted eye tracking data. Keywords—Head-mounted eye tracking technology, Aerial border surveillance, and search and rescue missions 

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5. Multi-Robot System for Autonomous Cooperative Counter-UAS Missions: Design, Integration, and Field Testing

   https://doi.org/10.1109/SSRR56537.2022.10018733  

   Barisic, Antonella; Ball, Marlan; Jackson, Noah; McCarthy, Riley; Naimi, Nasib; Strassle, Luca; Becker, Jonathan; Brunner, Maurice; Fricke, Julius; Markovic, Lovro; et al (November 2022, IEEE)

   With the rapid development of technology and the proliferation of uncrewed aerial systems (UAS), there is an immediate need for security solutions. Toward this end, we propose the use of a multi-robot system for autonomous and cooperative counter-UAS missions. In this paper, we present the design of the hardware and software components of different complementary robotic platforms: a mobile uncrewed ground vehicle (UGV) equipped with a LiDAR sensor, an uncrewed aerial vehicle (UAV) with a gimbal-mounted stereo camera for air-to-air inspections, and a UAV with a capture mechanism equipped with radars and camera. Our proposed system features 1) scalability to larger areas due to the distributed approach and online processing, 2) long-term cooperative missions, and 3) complementary multimodal perception for the detection of multirotor UAVs. In field experiments, we demonstrate the integration of all subsystems in accomplishing a counter-UAS task within an unstructured environment. The obtained results confirm the promising direction of using multi-robot and multi-modal systems for C-UAS. 

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