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Development and Optimization of Formation Flying for Unmanned Aerial Vehicles Using Particle Swarm Optimization Based on Reciprocal Velocity Obstacles
- Jun Hong Cheok - University of Nottingham, Department of Electrical and Electronic Engineering, Faculty of Science and Engineering, Malaysia ,
- Vimal Rau Aparow - University of Nottingham, Department of Electrical and Electronic Engineering, Faculty of Science and Engineering, Malaysia ,
- Juno Ng Zhi Neng - University of Nottingham, Department of Electrical and Electronic Engineering, Faculty of Science and Engineering, Malaysia ,
- Jian Lee Cheah - University of Nottingham, Department of Electrical and Electronic Engineering, Faculty of Science and Engineering, Malaysia ,
- Dickson Leong - University of Nottingham, Department of Electrical and Electronic Engineering, Faculty of Science and Engineering, Malaysia
Journal Article
01-15-02-0011
ISSN: 1946-3855, e-ISSN: 1946-3901
Sector:
Topic:
Citation:
Cheok, J., Aparow, V., Ng Zhi Neng, J., Cheah, J. et al., "Development and Optimization of Formation Flying for Unmanned Aerial Vehicles Using Particle Swarm Optimization Based on Reciprocal Velocity Obstacles," SAE Int. J. Aerosp. 15(2):171-184, 2022, https://doi.org/10.4271/01-15-02-0011.
Language:
English
Abstract:
In this article, a formation flying technique designed for a multiple unmanned
aerial vehicles (multi-UAV) system to provide low-cost and efficient solution
for civilian and military applications is presented. First, a modular
leader-follower formation algorithm was developed to accomplish the formation
flying with off-the-shelf low-cost components and sensors. Second, a
proportional-integral-derivative (PID) controller was utilized for velocity
control of the UAVs to maintain the tight formation. Third, a particle swarm
optimization-optimized reciprocal velocity obstacles (PSO-RVO) algorithm was
utilized for obstacles avoidance and collision avoidance between the UAVs while
navigating, with the aid of sonar ranging sensors onboard. The formation flying
algorithm developed was tested through both simulation and experiment using two
quadcopters with global positioning system (GPS) signals. For the simulation,
the algorithm developed was tested on a virtual quadcopter using an open-source
software-in-the-loop (SITL) simulator. With the aid of the experimental test,
the effectiveness of the proposed formation flying algorithm is evaluated. With
a separation distance of 5 m between the UAVs, the proposed system is able to
achieve an average separation error of 0.3872 m and percentage of root mean
square error (RMSE) of 9.7%. Therefore, it is shown that the proposed formation
flying system is very effective.