Unmanned aerial vehicles (UAVs) — also called drones — are used with increasing interest in civil and commercial applications. Drones can fly routes in an autonomous manner and carry cameras for aerial photography. Research and development efforts have recently addressed drone systems for monitoring, surveillance, or disaster assistance. Small-scale multicopters are of particular interest in this context due to their simple deployment, high maneuverability, and low costs. It is often beneficial to deploy a team of drones rather than a single drone, since multiple drones can explore areas faster. The research at our institute focuses on such multi-drone systems with emphasis on communication, coordination, and decision making.
“We focus on the design principles for a team of multiple aerial robots,” predoctoral researcher Samira Hayat explains and continues, “where a key question is how to integrate sensing, networking, and coordination on the resource-constrained drone platforms.” She explores the dependencies between the aerial flying paths and mission constraints on the communication performance among the drones and the base station. The goal is to establish and maintain a reliable aerial communication network.
The experimental evaluation of the developed methods and algorithms is an important objective. “We have successfully demonstrated our approach in a search-and-rescue prototype where four drones collaborate to find a person,” researcher Jürgen Scherer summarizes. “Depending on the prevailing situation, the drones explore the environment, perform target detection, and serve as communication relays,” he explains further. A dedicated multi-drone framework has been developed for the robot operating system (ROS).
Another use case involves employing a network of drones for delivery of important goods in remote areas. “Imagine a large disaster area in which medicine is required in some villages, but roads are flooded or destroyed,” Bettstetter argues. The question arises as how the jobs are allocated to many drones based on customer demand and locations of depots. Pasquale Grippa, a predoctoral researcher on this topic, is fascinated by the multidisciplinarity of his work. “It involves multi-agent systems, scheduling, logistics, queuing theory, and others,” he says.
This video shows a team of three UAVs autonomously covering a predefined region of interest and delivering the captured images to the base station where an overview image is generated in real-time.
S. Hayat, E. Yanmaz, and R. Muzaffar. Survey on unmanned aerial vehicle networks for civil applications: A communications viewpoint. IEEE Communications Surveys and Tutorials, 2016.
A. Khan, B. Rinner, and A. Cavallaro. Cooperative robots to observe moving targets: A review. IEEE Transactions on Cybernetics, 2016.
A. Khan, E. Yanmaz, and B. Rinner. Information exchange and decision making in micro aerial vehicle networks for cooperative search. IEEE Transactions on Control of Network Systems, 2015.
T. Andre, K. A. Hummel, A. P. Schoellig, E. Yanmaz, M. Asadpour, C. Bettstetter, P. Grippa, H. Hellwagner, S. Sand, and S. Zhang. Application-driven design of aerial communication networks. IEEE Communications Magazine, 2014.
E. Yanmaz, R. Kuschnig, and C. Bettstetter. Achieving air-ground communications in 802.11 networks with three-dimensional aerial mobility. In Proc. IEEE INFOCOM, 2013.
M. Quaritsch, K. Kruggl, D. Wischounig-Strucl, S. Bhattacharya, M. Shah, and B. Rinner. Networked UAVs as aerial sensor network for disaster management applications. e & i Elektrotechnik und Informationstechnik, 2010.