Improving time and energy efficiency in multi-UAV coverage operations by optimizing the UAVs’ initial positions
-
Published:2024-04-22
Issue:3
Volume:8
Page:629-647
-
ISSN:2366-5971
-
Container-title:International Journal of Intelligent Robotics and Applications
-
language:en
-
Short-container-title:Int J Intell Robot Appl
Author:
Stefanopoulou Aliki,Raptis Emmanuel K.,Apostolidis Savvas D.,Gkelios Socratis,Kapoutsis Athanasios Ch.,Chatzichristofis Savvas A.,Vrochidis Stefanos,Kosmatopoulos Elias B.
Abstract
AbstractThis paper focuses on Coverage Path Planning (CPP) methodologies, particularly in the context of multi-robot missions, to efficiently cover user-defined Regions of Interest (ROIs) using groups of UAVs, while emphasizing on the reduction of energy consumption and mission duration. Optimizing the efficiency of multi-robot CPP missions involves addressing critical factors such as path length, the number of turns, re-visitations, and launch positions. Achieving these goals, particularly in complex and concave ROIs with No-Go Zones, is a challenging task. This work introduces a novel approach to address these challenges, emphasizing the selection of launch points for UAVs. By optimizing launch points, the mission’s energy and time efficiency are significantly enhanced, leading to more efficient coverage of the selected ROIs. To further support our research and foster further exploration on this topic, we provide the open-source implementation of our algorithm and our evaluation mechanisms.
Funder
European Commission Democritus University of Thrace
Publisher
Springer Science and Business Media LLC
Reference32 articles.
1. Almadhoun, R., Taha, T., Seneviratne, L., Zweiri, Y.: A survey on multi-robot coverage path planning for model reconstruction and mapping. SN Appl. Sci. 1(8), 1–24 (2019) 2. Apostolidis, S.D., Kapoutsis, P.C., Kapoutsis, A.C., Kosmatopoulos, E.B.: Cooperative multi-uav coverage mission planning platform for remote sensing applications. Auton. Robot. 46(2), 373–400 (2022) 3. Apostolidis, S.D., Vougiatzis, G., Kapoutsis, A.C., Chatzichristofis, S.A., Kosmatopoulos, E.B.: Systematically improving the efficiency of grid-based coverage path planning methodologies in real-world uavs’ operations. Drones 7(6), 399 (2023) 4. Bähnemann, R., Lawrance, N., Chung, J.J., Pantic, M., Siegwart, R., Nieto, J.: Revisiting boustrophedon coverage path planning as a generalized traveling salesman problem. In: Bähnemann, R. (ed.) Field and Service Robotics, pp. 277–290. Springer, Cham (2021) 5. Bergstra, J., Bardenet, R., Bengio, Y., Kégl, B.: Algorithms for hyper-parameter optimization. In: Shawe-Taylor, J., Zemel, R., Bartlett, P., Pereira, F., Weinberger, K.Q. (eds.) Advances in Neural Information Processing Systems, vol. 24. Curran Associates, Inc. (2011). https://proceedings.neurips.cc/paper_files/paper/2011/file/86e8f7ab32cfd12577bc2619bc635690-Paper.pdf
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|