Trajectory Synthesis for a UAV Swarm Based on Resilient Data Collection Objectives

The use of Unmanned Aerial Vehicles (UAVs) for collecting data from remotely located sensor systems is emerging. The data can be time-sensitive and require to be transmitted to a data processing center. However, planning the trajectory for a swarm of UAVs depends on multi-fold constraints, such as d...

Full description

Saved in:
Bibliographic Details
Published in:IEEE eTransactions on network and service management 2023-03, Vol.20 (1), p.138-151
Main Authors: Jakaria, A. H. M., Rahman, Mohammad Ashiqur, Asif, Muneeba, Khalil, Alvi Ataur, Kholidy, Hisham A., Anderson, Matthew, Drager, Steven
Format: Article
Language:English
Subjects:
Autonomous aerial vehicles
Data collection
Data points
Data processing
formal model
Fuels
Maneuvers
Planning
Remote sensors
Resilience
resiliency
sensor data collection
Synthesis
Three-dimensional displays
Topology
Trajectory
Trajectory analysis
trajectory design
Trajectory planning
UAV swarm
Unmanned aerial vehicles
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The use of Unmanned Aerial Vehicles (UAVs) for collecting data from remotely located sensor systems is emerging. The data can be time-sensitive and require to be transmitted to a data processing center. However, planning the trajectory for a swarm of UAVs depends on multi-fold constraints, such as data collection requirements, UAV maneuvering capacities, and budget limitations. Since a UAV may fail or be compromised, it is important to provide necessary resilience to such contingencies, thus ensuring data security. It is important to provide the UAVs with efficient spatio-temporal trajectories so that they can efficiently cover necessary data sources. In this work, we present Synth4UAV, a formal approach for automated synthesis of efficient trajectories for a UAV swarm by logically modeling the aerial space and data point topology, UAV moves, and associated constraints in terms of the turning and climbing angle, fuel usage, data collection point coverage, data freshness, and resiliency properties. We use efficient, logical formulas to encode and solve the complex model. The solution to the model provides the routing and maneuvering plan for each UAV, including the time to visit the points on the paths and corresponding fuel usage such that the necessary data points are visited while satisfying the resiliency requirements. We evaluate the proposed trajectory synthesizer, and the results show that the relationship among different parameters follows the requirements while the tool scales well with the problem size.
ISSN:1932-4537
1932-4537
DOI:10.1109/TNSM.2022.3216804