TY - JOUR
T1 - DAGmap
T2 - Multi-Drone SLAM via a DAG-Based Distributed Ledger
AU - Park, Seongjoon
AU - Kim, Hwangnam
N1 - Funding Information:
This research was supported by the Ministry of Science and ICT (MSIT), Korea, under the Information Technology Research Center (ITRC) support program (IITP-2021-0-01835) supervised by the Institute of Information & Communications Technology Planning & Evaluation (IITP), and the Human Resources Program in Energy Technology of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry & Energy (MOTIE) of the Republic of Korea (no. 20204010600220).
Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2022/2
Y1 - 2022/2
N2 - Simultaneous localization and mapping (SLAM) in unmanned vehicles, such as drones, has great usability potential in versatile applications. When operating SLAM in multi-drone scenarios, collecting and sharing the map data and deriving converged maps are major issues (regarded as the bottleneck of the system). This paper presents a novel approach that utilizes the concepts of distributed ledger technology (DLT) for enabling the online map convergence of multiple drones without a centralized station. As DLT allows each agent to secure a collective database of valid transactions, DLT-powered SLAM can let each drone secure global 3D map data and utilize these data for navigation. However, block-based DLT—a so called blockchain—may not fit well to the multi-drone SLAM due to the restricted data structure, discrete consensus, and high power consumption. Thus, we designed a multi-drone SLAM system that constructs a DAG-based map database and sifts the noisy 3D points based on the DLT philosophy, named DAGmap. Considering the differences between currency transactions and data constructions, we designed a new strategy for data organization, validation, and a consensus framework under the philosophy of DAG-based DLT. We carried out a numerical analysis of the proposed system with an off-the-shelf camera and drones.
AB - Simultaneous localization and mapping (SLAM) in unmanned vehicles, such as drones, has great usability potential in versatile applications. When operating SLAM in multi-drone scenarios, collecting and sharing the map data and deriving converged maps are major issues (regarded as the bottleneck of the system). This paper presents a novel approach that utilizes the concepts of distributed ledger technology (DLT) for enabling the online map convergence of multiple drones without a centralized station. As DLT allows each agent to secure a collective database of valid transactions, DLT-powered SLAM can let each drone secure global 3D map data and utilize these data for navigation. However, block-based DLT—a so called blockchain—may not fit well to the multi-drone SLAM due to the restricted data structure, discrete consensus, and high power consumption. Thus, we designed a multi-drone SLAM system that constructs a DAG-based map database and sifts the noisy 3D points based on the DLT philosophy, named DAGmap. Considering the differences between currency transactions and data constructions, we designed a new strategy for data organization, validation, and a consensus framework under the philosophy of DAG-based DLT. We carried out a numerical analysis of the proposed system with an off-the-shelf camera and drones.
KW - DAG-based DLT
KW - Distributed ledger technology
KW - Multi-agent SLAM
UR - http://www.scopus.com/inward/record.url?scp=85123795718&partnerID=8YFLogxK
U2 - 10.3390/drones6020034
DO - 10.3390/drones6020034
M3 - Article
AN - SCOPUS:85123795718
SN - 2504-446X
VL - 6
JO - Drones
JF - Drones
IS - 2
M1 - 34
ER -