Distributed Cooperative Collision‐Free Tracking Control for 30 Quadrotors Under Internal and External Threats

ABSTRACT The high efficiency of multiple quadrotors coordination makes it widely used. However, the technology faces threats from internal collisions as well as external obstacles. This paper proposes a multiquadrotors distributed cooperative collision‐free tracking control framework, which consists of three parts: collision avoidance mechanism, obstacle avoidance mechanism and tracking control. First, in the face of internal and external threats, the collision avoidance function with damping is designed based on Hooke's law. And the potential energy function is designed for multiple quadrotors obstacle avoidance based on bird flock obstacle avoidance. Then, a distributed control protocol is proposed based on consensus theory. Finally, a multi‐quadrotors simulation and experiment platform with the same architecture is built. We deploy the framework on the multiple quadrotor platform and conduct collision avoidance, obstacle avoidance, and encirclement experiments with 30 quadrotors. The experimental results show that the quadrotors can perform the task well. The minimum distance between quadrotors is 0.8022 m, and the minimum distance from obstacles is 0.8866 m, all of which meet the safety distance requirements. Moreover, compared with classical and advanced methods in simulation, our proposed method has the smallest average tracking error, only 0.3019 m, and improves task time by 7.03% and 6.23%, respectively, which verifies the effectiveness and practicality of the proposed framework of distributed cooperative collision avoidance and tracking control for multiple quadrotors.

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Publication Details

Journal
Journal of Field Robotics
Published
2024-12-30
DOI
https://doi.org/10.1002/rob.22502
Citations
1
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.35

Funders

Controls
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article

Distributed Cooperative Collision‐Free Tracking Control for 30 Quadrotors Under Internal and External Threats

Mingming Wang, Yuan Ping, Jinjin Guo, Chong Wu et al.
1 citations
Journal of Field Robotics
Distributed Control Multi-Agent Systems
0.35
article

Distributed Cooperative Collision‐Free Tracking Control for 30 Quadrotors Under Internal and External Threats

Mingming Wang, Yuan Ping, Jinjin Guo, Chong Wu, Juntong Qi, Yan Peng, Guang Yang
article en
1 citations

Abstract

ABSTRACT The high efficiency of multiple quadrotors coordination makes it widely used. However, the technology faces threats from internal collisions as well as external obstacles. This paper proposes a multiquadrotors distributed cooperative collision‐free tracking control framework, which consists of three parts: collision avoidance mechanism, obstacle avoidance mechanism and tracking control. First, in the face of internal and external threats, the collision avoidance function with damping is designed based on Hooke's law. And the potential energy function is designed for multiple quadrotors obstacle avoidance based on bird flock obstacle avoidance. Then, a distributed control protocol is proposed based on consensus theory. Finally, a multi‐quadrotors simulation and experiment platform with the same architecture is built. We deploy the framework on the multiple quadrotor platform and conduct collision avoidance, obstacle avoidance, and encirclement experiments with 30 quadrotors. The experimental results show that the quadrotors can perform the task well. The minimum distance between quadrotors is 0.8022 m, and the minimum distance from obstacles is 0.8866 m, all of which meet the safety distance requirements. Moreover, compared with classical and advanced methods in simulation, our proposed method has the smallest average tracking error, only 0.3019 m, and improves task time by 7.03% and 6.23%, respectively, which verifies the effectiveness and practicality of the proposed framework of distributed cooperative collision avoidance and tracking control for multiple quadrotors.

Journal of Field RoboticsVol. 42(3)
Shanghai University (CN), Tianjin University (CN), China Electronics Technology Group Corporation (CN), Beijing Academy of Artificial Intelligence (CN), Hainan Agricultural School (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 35%
Distributed Control Multi-Agent Systems
0.35
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