TY - JOUR
T1 - Distributed Formation Planning for Unmanned Aerial Vehicles
AU - Zhao, Zeming
AU - Zhang, Xiaozhen
AU - Fang, Hao
AU - Yang, Qingkai
N1 - Publisher Copyright:
© 2025 by the authors.
PY - 2025/4
Y1 - 2025/4
N2 - 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.
AB - 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.
KW - path searching
KW - trajectory optimization
KW - UAV formation
UR - http://www.scopus.com/inward/record.url?scp=105003556683&partnerID=8YFLogxK
U2 - 10.3390/drones9040306
DO - 10.3390/drones9040306
M3 - Article
AN - SCOPUS:105003556683
SN - 2504-446X
VL - 9
JO - Drones
JF - Drones
IS - 4
M1 - 306
ER -