Cooperative control of multi-UAV with time constraint in the threat environment

Ma, Peifeng; Zuo-e, Fan; Ji, Jun

doi:10.1109/cgncc.2014.7007549

Cited by 4 publications

(2 citation statements)

References 2 publications

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“…In addition, another approach is to plan the paths under the constraints of the rendezvous time. Ma et al [29] used the improved Dijkstra algorithm to plan the rendezvous paths for UAVs in a two-dimensional environment. However, such methods are difficult to scale to high-dimensional systems.…”

Section: Related Workmentioning

confidence: 99%

Decentralized Multi-UAV Path Planning Based on Two-Layer Coordinative Framework for Formation Rendezvous

2022

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Unmanned aerial vehicle (UAV) formation rendezvous path planning problem is one of the important research topics in multiple UAV (multi-UAV) coordinated path planning. Aiming at solving low computational efficiency and poor scalability of the traditional multi-UAV path planning method, the decentralized multi-UAV path planning method suitable for obstacle environments is proposed. Firstly, the UAV rendezvous path planning problem with constraints such as the kinematics of UAVs and collision-free constraints is modeled as a non-convex optimal control problem. To minimize formation rendezvous time and energy consumption, a two-layer coordinative framework is developed to solve this problem. In the coordination layer, relying only on the information of neighboring UAVs, each UAV in the decentralized communication graph negotiates the desired flight time using a consensus protocol to achieve coordination among UAVs. In the planning layer, the initial non-convex formation rendezvous path planning problem is decoupled into several sub-problems, which can be solved in parallel by path planners distributed on each UAV using sequential convex programming. Finally, numerical simulations are carried out to verify the effectiveness and scalability of the proposed method. The results show that this decentralized multi-UAV path planning method can handle the minimum-time rendezvous path planning problem and optimize the energy consumption in flight, and the computing time does not increase significantly with the enlargement of the UAV swarm. This decentralized framework scales well with the number of UAVs and can be applied for future urban flight and supplies delivery tasks.INDEX TERMS Unmanned aerial vehicle, path planning, decentralized coordination, sequential convex programming, collision-free.

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Section: Related Workmentioning

confidence: 99%

Decentralized Multi-UAV Path Planning Based on Two-Layer Coordinative Framework for Formation Rendezvous

2022

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“…Multiple UAVs sharing information and searching cooperatively can improve the efficiency of task execution. In the process of the search task, the path planning of the multi-UAV is a crucial problem [3].…”

Section: Introductionmentioning

confidence: 99%

Cooperative Search Method for Multiple UAVs Based on Deep Reinforcement Learning

Gao

Zhang

2022

Sensors

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In this paper, a cooperative search method for multiple UAVs is proposed to solve the problem of low efficiency of multi-UAV task execution by using a cooperative game with incomplete information. To improve search efficiency, CBBA (Consensus-Based Bundle Algorithm) is applied to designate the tasks area for each UAV. Then, Independent Deep Reinforcement Learning (IDRL) is used to solve Nash equilibrium to improve UAVs’ collaborations. The proposed reward function is smartly developed to guide UAVs to fly along the path with higher reward value while avoiding the collisions between UAVs during flights. Finally, extensive experiments are carried out to compare our proposed method with other algorithms. Simulation results show that the proposed method can obtain more rewards in the same period of time as other algorithms.

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A Space-Time Harmonic Potential-Based Navigation Control With Guaranteed Time of Arrival and Obstacle Avoidance

Masoud

2023

IEEE Trans. Automat. Sci. Eng.

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Cooperative control of multi-UAV with time constraint in the threat environment

Cited by 4 publications

References 2 publications

Decentralized Multi-UAV Path Planning Based on Two-Layer Coordinative Framework for Formation Rendezvous

Decentralized Multi-UAV Path Planning Based on Two-Layer Coordinative Framework for Formation Rendezvous

Cooperative Search Method for Multiple UAVs Based on Deep Reinforcement Learning

A Space-Time Harmonic Potential-Based Navigation Control With Guaranteed Time of Arrival and Obstacle Avoidance

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