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Abstract
Unmanned Aerial Vehicles (UAVs) can be a powerful tool for live (interactive) remote inspection of large-scale structures or areas of interest. Instead of manual, local, and labor-intensive inspections, we envision human operators working together with networks of semi-autonomous UAVs. The current state-of-the-art for low-delay high-throughput inter-vehicle networking relies on Time-Division Multiple Access (TDMA) techniques that require accurate synchronization among all network nodes. In this paper, we propose a delay-tolerant synchronization approach that converges to the correct order of the TDMA slots implemented over COTS WiFi in a fully-distributed way and without resorting to a global clock. This highly flexible solution allows building an ad-hoc aerial network based on a backbone of relaying UAVs. We show several alternatives to achieve this synchronization in a concrete aerial network and compare them in terms of slots’ overlap, throughput, and packet delivery. The results show that these alternatives lead to trade-offs in the referenced metrics. The results also provide insight into the delays caused by buffering in the protocol stack and especially in the WiFi interface.
Highlights
Unmanned Aerial Vehicles (UAVs), in particular multirotors, can be used for a myriad of applications such as live remote inspection of large-scale structures, e.g., towers, bridges, pipelines, or of specific areas of interest, e.g., for search and rescue [1] or wild-life surveys [2]
We propose a delay-tolerant synchronization approach that converges to the correct order of the Time-Division Multiple Access (TDMA) slots implemented over COTS WiFi in a fully-distributed way and without resorting to a global clock
In the case of a network relying on a shared medium, such as Radio Frequency (RF), TDMA provides a separate slot to every transmitter in the network, preventing mutual interference
Summary
Unmanned Aerial Vehicles (UAVs), in particular multirotors, can be used for a myriad of applications such as live (interactive) remote inspection of large-scale structures, e.g., towers, bridges, pipelines, or of specific areas of interest, e.g., for search and rescue [1] or wild-life surveys [2]. An operator at a ground Base Station (BS) defines a remote Area-of-Interest (AoI) and instructs a group of semi-autonomous sensor-capable UAVs to navigate there; secondly, interactive control of the fine position and pose of UAVs is initiated to focus on features of interest; concurrently, a live stream of sensor data from the AoI to the BS is initiated; the necessary communication backbone is established, by means of a complementary autonomous group of relaying UAVs, linking sensor UAVs to the BS
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