PRE2017 3 Group 17 - State of the Art
State of the art report for the project of PRE2017 3 Groep17.
Image stitching
Drone flying and controlling
Swarm
We found an article describing two “cleaning” algorithms for swarms of robots. It explains how these algorithms can be used as “hunting” protocols to, for instance, find lost humans. The first of the two algorithms, Parallel Path Search, works on rectangular areas only and requires them to have no “leakage”, but is computationally quite light. Leakage is a term used to describe the phenomenon of dirt leaking from dirty sectors to clean sectors or, closer to the example, the opportunity for a fugitive to escape when gaps between drones are too large. The second, the SWEEP protocol, on the other hand, will work on any non-disconnected area and can work around "leakage", but is computationally quite expensive at times and requires an overview of the entire area. The DDDAS framework uses the best of Parallel Path Search and the SWEEP protocol to create a better framework, that also takes potential loss of drones into account. All in all, some very interesting algorithms already exist for the theme in mind.[1]
Sensors and analysis methods
The first article of belonging to the category presents a list of different sensors and camera's that are currently available for drone flight and sectors where they are used often. These consist of, but are not limited to, accellerometers, cameras (both infrared and normal) and GPS.[2]
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