Piecewise-potential-field-based path planning method for fixed-wing UAV formation
TL;DR: In this paper , a fixed-wing UAV formation path planning method based on piecewise potential field (PPF) is proposed, where the problem of formation flight path planning in different states can be solved by suitable design of the PPF function.
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Abstract: 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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Citations
Research on Multi-UAV Obstacle Avoidance with Optimal Consensus Control and Improved APF
TL;DR: Optimal consensus control and improved APF for multi-UAV obstacle avoidance. Novel formation control method integrating UAV maneuver constraints with consensus formation control and optimal velocity control through PSO. Improved obstacle avoidance algorithms based on virtual force fields and collinear force deflection angles. Enhanced formation convergence performance and mitigation of local optimal solutions.
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Multi-UAV Path Planning Based on Cooperative Co-Evolutionary Algorithms with Adaptive Decision Variable Selection
TL;DR: This study proposes CCEA-ADVS, a novel algorithm for multi-UAV path planning, which decomposes high-dimensional variables, introduces an adaptive decision variable selection strategy, and adopts a two-stage evolutionary optimization process to improve computational efficiency and convergence speed.
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Fixed-Wing UAV Formation Path Planning Based on Formation Control: Theory and Application
TL;DR: A novel millisecond-level path planning method appropriate for large-scale fixed-wing UAV formation, which consists of two parts, that can not only achieve millisecond-level path planning for the entire formation but also excellently maintain formation during the flight.
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TL;DR: Simulation results present the possibilities of applying the APF method to holonomic UAVs such as quadcopters and show that such UAVs controlled on the basis of an APF behave as non-holonomic UAVs during 90° turns.
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