View : 570 Download: 0
Towards Persistent Surveillance and Reconnaissance Using a Connected Swarm of Multiple UAVs
- Title
- Towards Persistent Surveillance and Reconnaissance Using a Connected Swarm of Multiple UAVs
- Authors
- Cho, Jeihee; Sung, Jaeyi; Yoon, Jinyi; Lee, Hyungjune
- Ewha Authors
- 이형준
- SCOPUS Author ID
- 이형준
- Issue Date
- 2020
- Journal Title
- IEEE ACCESS
- ISSN
- 2169-3536
- Citation
- IEEE ACCESS vol. 8, pp. 157906 - 157917
- Keywords
- Surveillance; Data collection; Sensors; Reconnaissance; Unmanned aerial vehicles; Navigation; Mobile agents; Persistent surveillance; reconnaissance; connected UAVs; mobile sensor networks; swarm exploration
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Indexed
- SCIE; SCOPUS
- Document Type
- Article
- Abstract
- In situations where surveillance or communication infrastructure has collapsed, it is important to keep monitoring affected areas. We leverage unmanned aerial vehicles (UAVs) to collect and provide up-to-date on-site information to a data consumer in an efficient way, for later complete yet agile analysis. We propose a distributed dynamic data collection scheme for persistent surveillance and reconnaissance, using a swarm of connected UAVs with two phases of operation: 1) network formation; and 2) UAV traversal of a region of interest. The main task of a UAV is to continuously collect data within its sensing range, while the UAV swarm travels along the calculated paths. When UAVs are newly connected to form a swarm, or disconnected from an already-formed swarm, a formation phase begins. In the formation phase, UAVs become a single group and produce a compact, dynamically alternating formation called DiagonalX to cover broad areas, including boundary parts, in a fair and effective manner. During the traversal phase, each UAV swarm finds a simple yet efficient navigation path based on data freshness to cover sub-areas and continuously obtain up-to-date information evenly throughout the whole region of interest. Simulation experiments confirm that both formation and traversal procedures perform essential tasks in a distributed manner, while maintaining better data freshness than other counterpart algorithms, with a freshness factor of up to 5.77, and reasonable overheads. An additional feature, a dynamically aperiodic formation change, achieves a more stable performance.
- DOI
- 10.1109/ACCESS.2020.3019963
- Appears in Collections:
- 인공지능대학 > 컴퓨터공학과 > Journal papers
- Files in This Item:
There are no files associated with this item.
- Export
- RIS (EndNote)
- XLS (Excel)
- XML