A Coverage Path Planning Algorithm for Self-Organizing Drone Swarms (bibtex)
by Konstantinos Bezas, Konstantinos Oikonomou, Georgios Tsoumanis
Abstract:
Drone swarms are employed for multiple applications nowadays, such as early detection of forest fires, disaster response missions etc., area coverage being the main hurdle these applications face. In this work, an algorithm is proposed for drone swarms that achieves full area coverage and Point of Interest (PoI) detection with no decomposition for areas with simple polygon shapes and no obstacles. It employs small pieces of information that are exchanged among the swarm drones in real-time. Parallel lines and spiral coverage paths are examined in terms of the number of slowdowns in the swarms speed to fully collect information from a detected PoI, the scanned PoIs, and the formation switches that are executed when the swarm has to alter its flying direction. Simulations are developed for a square area shape. The results showcase that the parallel coverage path is more efficient in terms of cover time and travel distance compared to the spiral. The parallel coverage requires less slowdowns for the same percentage of scanned PoIs.
Reference:
Konstantinos Bezas, Konstantinos Oikonomou, Georgios Tsoumanis, "A Coverage Path Planning Algorithm for Self-Organizing Drone Swarms", In 2021 International Balkan Conference on Communications and Networking (BalkanCom), Novi Sad, Serbia, pp. 122-126, 2021.
Bibtex Entry:
@inproceedings{bezas2021coverage,
	abstract = {Drone swarms are employed for multiple applications nowadays, such as early
detection of forest fires, disaster response missions etc., area coverage
being the main hurdle these applications face. In this work, an algorithm
is proposed for drone swarms that achieves full area coverage and Point of
Interest (PoI) detection with no decomposition for areas with simple
polygon shapes and no obstacles. It employs small pieces of information
that are exchanged among the swarm drones in real-time. Parallel lines and
spiral coverage paths are examined in terms of the number of slowdowns in
the swarms speed to fully collect information from a detected PoI, the
scanned PoIs, and the formation switches that are executed when the swarm
has to alter its flying direction. Simulations are developed for a square
area shape. The results showcase that the parallel coverage path is more
efficient in terms of cover time and travel distance compared to the
spiral. The parallel coverage requires less slowdowns for the same
percentage of scanned PoIs.},
	address = {Novi Sad, Serbia},
	author = {Konstantinos Bezas and Konstantinos Oikonomou and Georgios Tsoumanis},
	booktitle = {2021 International Balkan Conference on Communications and Networking (BalkanCom)},
	date-added = {2021-08-31 16:43:06 +0300},
	date-modified = {2021-12-06 10:41:21 +0200},
	doi = {10.1109/BalkanCom53780.2021.9593145},
	keywords = {own, refereed, v-corfu, R:ID:DS, R:IOT:UAV},
	month = 9,
	pages = {122-126},
	title = {{{A Coverage Path Planning Algorithm for {Self-Organizing} Drone Swarms}}},
	year = 2021,
	Bdsk-Url-1 = {https://doi.org/10.1109/BalkanCom53780.2021.9593145}}
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