Dynamic collision avoidance for cooperative fixed-wing UAV swarm based on normalized artificial potential field optimization

Liu, Wei-heng; Xin, Zheng; Deng, Zhihong

doi:10.1007/s11771-021-4840-5

Cited by 17 publications

(6 citation statements)

References 33 publications

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“…The artificial potential field algorithm can obtain real-time distance information of obstacles through ultrasonic sensors to achieve obstacle avoidance. The principle of the artificial potential field [9][10] is to abstract the motion environment around the device into the motion in the gravitational repulsion field, as shown in the schematic diagram. From the beginning to the end there is a gravitational potential field for the device, denoted as U a .…”

Section: Obstacle Avoidance Algorithm Based On Artificial Potential F...mentioning

confidence: 99%

Research on surface garbage collection device based on YOLOv7

Yuan,

Chen,

et al. 2024

Third International Conference on High Performance Computing and Communication Engineering (HPCCE 2023)

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Section: Obstacle Avoidance Algorithm Based On Artificial Potential F...mentioning

confidence: 99%

Research on surface garbage collection device based on YOLOv7

Yuan,

Chen,

et al. 2024

Third International Conference on High Performance Computing and Communication Engineering (HPCCE 2023)

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“…The latest research of Liu et al can avoid the local minimum problem and the local oscillation of trajectory by constructing a novel APF function with anisotropy in each dimension. This study also proposed a target vector decomposition strategy to avoid dynamic obstacles and sudden threats in advance, so that the planned trajectory does not have a segment with sharp changes in normal acceleration, but this study focuses on the cooperation of multiple aircraft where the problem of formation flight of multiple UAVs has not been studied 46 .…”

Section: Related Workmentioning

confidence: 99%

Piecewise-potential-field-based path planning method for fixed-wing UAV formation

Fang

Yao

Zhu

et al. 2023

Sci Rep

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The multi-UAV path planning method based on artificial potential field (APF) has the advantage of rapid processing speed and the ability to deal with dynamic obstacles, though some problems remain—such as a lack of consideration of the initial heading constraint of the UAVs, making it easy to fall into a local minimum trap, and the path not being sufficiently smooth. Consequently, a fixed-wing UAV formation path planning method based on piecewise potential field (PPF) is proposed, where the problem of UAV formation flight path planning in different states can be solved by suitable design of the PPF function. Firstly, the potential field vector can be used to represent the potential field functions of obstacles and target points to meet the kinematic constraints of the UAV. Secondly, the local minimum region can be detected, the additional potential field vector being set to break away from this region. Finally, the change rules of the potential field vector of a UAV in the formation reconstruction scene can be designed, a smooth formation flight track being assured by adjusting the corresponding speed of each UAV track point. Considering the path planning of a five-UAV formation as an example, we conducted simulation experiments. The results showed that—compared with the existing methods based on APF—the results obtained using the PPF-based method considered the initial heading limits of the UAVs, the planned path being considerably smoother. Moreover, the proposed method could plan multiple UAV tracks, satisfying the known constraints without conflict in complex scenarios.

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“…In order to accurately describe the path planning process of UAV, its two-dimensional environment map [15,16] needs to be modeled.…”

Section: Environmental Modelmentioning

confidence: 99%

Path Planning of Multirotor UAV Based on the Improved Ant Colony Algorithm

Zhang

Zhang³

2022

Journal of Robotics

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Path planning is an important part of the unmanned aerial vehicle (UAV) to realize its autonomous capabilities. Aiming at the shortcomings of the traditional ant colony algorithm-based trajectory planning method, which has slow convergence speed and easy to fall into the local optimum, a path planning method based on the improved ant colony algorithm is proposed. First, a dynamic adjusting factor is added into the heuristic function to improve the directivity of path selection and search speed. Then, the state transition strategy is improved to solve the problem of slow convergence in the initial stage and easy to fall into local optimum in the later stage. Finally, the path inflection point is smoothly optimized through the cubic B-spline curve. Simulation results show that the improved ant colony algorithm can quickly converge to the optimal path and well adapt to the flight requirements of multirotor UAV.

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Dynamic collision avoidance for cooperative fixed-wing UAV swarm based on normalized artificial potential field optimization

Cited by 17 publications

References 33 publications

Research on surface garbage collection device based on YOLOv7

Research on surface garbage collection device based on YOLOv7

Piecewise-potential-field-based path planning method for fixed-wing UAV formation

Path Planning of Multirotor UAV Based on the Improved Ant Colony Algorithm

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