Distributed Formation Planning for Unmanned Aerial Vehicles

Formation flying of multiple unmanned aerial vehicles (UAVs) has attracted much attention for its versatility in cooperative tasks. In this paper, a distributed formation planning method is proposed for UAVs. First, we design a path searching algorithm, swarm-A*, which can enhance the cohesion of a swarm, i.e., preventing the disintegration of the swarm when it encounters an obstacle. Then, after waypoint reallocation, a formation trajectory optimization framework is formulated. Smooth formation trajectories for UAVs to travel safely in obstacle-laden environments can be obtained by solving the optimization problem. Next, a tracking controller based on sliding mode control is designed, ensuring that the UAVs follow the planned formation trajectories under dynamic constraints. Finally, numerical simulations and experiments are conducted to validate the effectiveness of the proposed method.

Authors

Institutions

Publication Details

Journal
Drones
Published
2025-04-14
DOI
https://doi.org/10.3390/drones9040306
Citations
4
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
5.10

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Distributed Formation Planning for Unmanned Aerial Vehicles

Zeming Zhao, Qingkai Yang, Xiaozhen Zhang
4 citations
Drones
Robotic Path Planning Algorithms
5.10
article

Distributed Formation Planning for Unmanned Aerial Vehicles

Zeming Zhao, Qingkai Yang, Xiaozhen Zhang
article en
4 citations

Abstract

Formation flying of multiple unmanned aerial vehicles (UAVs) has attracted much attention for its versatility in cooperative tasks. In this paper, a distributed formation planning method is proposed for UAVs. First, we design a path searching algorithm, swarm-A*, which can enhance the cohesion of a swarm, i.e., preventing the disintegration of the swarm when it encounters an obstacle. Then, after waypoint reallocation, a formation trajectory optimization framework is formulated. Smooth formation trajectories for UAVs to travel safely in obstacle-laden environments can be obtained by solving the optimization problem. Next, a tracking controller based on sliding mode control is designed, ensuring that the UAVs follow the planned formation trajectories under dynamic constraints. Finally, numerical simulations and experiments are conducted to validate the effectiveness of the proposed method.

DronesVol. 9(4)
Beijing Institute of Technology (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 5%
Robotic Path Planning Algorithms
5.10
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Distributed Formation Planning for Unmanned Aerial Vehicles — Zeming Zhao, Qingkai Yang, et al. · Drones (2025) | TGRS Research Map | TGRS