Abstract
With the number and variety of commercial drones and UAVs (Unmanned Aerial Vehicles) set to escalate, there will be high future demands on popular regions of airspace and communication bandwidths. This raises safety concerns and hence heightens the need for a generic quantitative understanding of the real-time dynamics of multi-drone populations. Here, we explain how a simple system design built around system-level competition, as opposed to cooperation, can be used to control and ultimately reduce the fluctuations that ordinarily arise in such congestion situations, while simultaneously keeping the on-board processing requirements minimal. These benefits naturally arise from the collective competition to choose the less crowded option, using only previous outcomes and built-in algorithms. We provide explicit closed-form formulae that are applicable to any number of airborne drones N, and which show that the necessary on-board processing increases slower than N as N increases. This design therefore offers operational advantages over traditional cooperative schemes that require drone-to-drone communications that scale like N 2 , and also over optimization and control schemes that do not easily scale up to general N. In addition to populations of drones, the same mathematical analysis can be used to describe more complex individual drones that feature N adaptive sensor/actuator units.
Highlights
Like many other cyber-physical systems, the development of drones—which we take here for convenience as including UAV (Unmanned Aerial Vehicle) systems—is growing at a remarkable rate [1,2,3,4,5,6,7] in terms of on-board sensing, computing, communication, hovering and locomotion capabilities
Civilian drones vastly outnumber military drones, and there is an upward trend with the Federal Aviation Administration (FAA) estimating that consumer sales could grow from
Just as happens with regular road traffic, they will likely often be trying to access the same part of airspace, or send messages using the same bandwidth range, meaning that they can produce congestion and potential traffic pile-ups as in regular road traffic but with the added risk that they may fall out of the sky Electronics 2017, 6, 31; doi:10.3390/electronics6020031
Summary
Like many other cyber-physical systems, the development of drones—which we take here for convenience as including UAV (Unmanned Aerial Vehicle) systems—is growing at a remarkable rate [1,2,3,4,5,6,7] in terms of on-board sensing, computing, communication, hovering and locomotion capabilities. We propose here a different approach that is built around collective competition and only requires feedback of global information about overall system behavior, as opposed to the requirements for real-time cooperation between individual drones It eliminates the need for costly drone-to-drone communications, which, for a population of N drones, would require keeping open approximately N ( N − 1)/2 ∼ N 2 possible communication links. Though Scenario 2 is not realistic given current technology, it instead is aimed at exploring a futuristic possibility inspired by living systems It is known [11] that Drosophila larvae show remarkable abilities in terms of being able to regulate and balance the tasks for movement, momentary stationarity and turning, without the potentially costly overhead of a large, centralized control. We continue this paper with a forward-looking discussion of future generation scenarios in which decentralization is the preferred choice
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