Multi-UAV Adaptive Path Planning in Complex Environment Based on Behavior Tree

Wu, Wendi; Li, Jinghua; Wu, Yunlong; Ren, Xiuyan; Tang, Yuhua

doi:10.1007/978-3-030-67540-0_32

Cited by 3 publications

(3 citation statements)

References 9 publications

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“…In the process, the trajectory is corrected according to the motion constraints and control errors of the UAV so as to make full use of real-time feedback information to gradually generate a global trajectory. Figure 28 Wu et al [161] proposed a behavior tree (BT) model. The specific operation is to combine the model prediction with the decision tree to obtain the behavior tree (BT).…”

Section: Mathematical Optimization Algorithmmentioning

confidence: 99%

“…Table 10 summarizes the contents of our survey on model predictive control algorithms. Wu et al [161] proposed a behavior tree (BT) model. The specific operation is to combine the model prediction with the decision tree to obtain the behavior tree (BT).…”

Section: Mathematical Optimization Algorithmmentioning

confidence: 99%

“…The model uses the collision probability algorithm and the Kalman filter algorithm for UAV collision probability calculation and formation state estimation, and it calculates feasible trajectories for UAV formation in real time. It also addressed possible trajectory conflicts in high-density drone formations.Wu et al[161] proposed a behavior tree (BT) model. The specific operation is to combine the model prediction with the decision tree to obtain the behavior tree (BT).…”

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confidence: 99%

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UAV Formation Trajectory Planning Algorithms: A Review

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With the continuous development of UAV technology and swarm intelligence technology, the UAV formation cooperative mission has attracted wide attention because of its remarkable function and flexibility to complete complex and changeable tasks, such as search and rescue, resource exploration, reconnaissance and surveillance. The collaborative trajectory planning of UAV formation is a key part of the task execution. This paper attempts to provide a comprehensive review of UAV formation trajectory planning algorithms. Firstly, from the perspective of global planning and local planning, a simple framework of the UAV formation trajectory planning algorithm is proposed, which is the basis of comprehensive classification of different types of algorithms. According to the proposed framework, a classification method of existing UAV formation trajectory planning algorithms is proposed, and then, different types of algorithms are described and analyzed statistically. Finally, the challenges and future research directions of the UAV formation trajectory planning algorithm are summarized and prospected according to the actual requirements. It provides reference information for researchers and workers engaged in the formation flight of UAVs.

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Section: Mathematical Optimization Algorithmmentioning

confidence: 99%

Section: Mathematical Optimization Algorithmmentioning

confidence: 99%

mentioning

confidence: 99%

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UAV Formation Trajectory Planning Algorithms: A Review

Yang

Xiong

Yan

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Talking to Autonomous Drones: Command and Control Based on Hierarchical Task Decomposition

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2021 International Conference on Unmanned Aircraft Systems (ICUAS)

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The Routes of Unmanned Aerial Vehicle Planning Methods Ontology

Chumak,

Dudko,

Dmitriiev

2024

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The article analyzes modern methods of the route of unmanned aerial vehicles (UAVs) planning. An ontology for the routes of the UAVs group planning algorithms classification has been developed, which includes two elements: global planning and local planning. The article notes that the purpose of UAV flight routes planning is the optimal (rational) solution of specific tasks under appropriate weather conditions and taking into account other factors of the external environment. According to the premise of taking into account a significant number of constraints, the objective function of planning is to reach each UAV from the group to the end point (mission point). Planning the UAVs group route is a complex task of its multi-criteria optimization and solution in the presence of constraints. With the increase in the UAVs number, the analytical space of the route planning task will grow exponentially. The existing methods of planning the of the UAVs group movement route have a number of disadvantages, therefore, the development of a comprehensive method that reduces computational requirements, saves time, allows to plan routes in real time, and is also more effective from the group's mission performance point of view. The article defines the requirements for the UAVs group routes planning promising methods: complex modeling of many factors of the external environment influence; planning in real time; integration of planning methods. Combining the characteristics of heuristic algorithms and machine learning methods also allows you to obtain complex methods that have a higher adaptability to the conditions of the external environment and expand the range of applications.

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Multi-UAV Adaptive Path Planning in Complex Environment Based on Behavior Tree

Cited by 3 publications

References 9 publications

UAV Formation Trajectory Planning Algorithms: A Review

UAV Formation Trajectory Planning Algorithms: A Review

Talking to Autonomous Drones: Command and Control Based on Hierarchical Task Decomposition

The Routes of Unmanned Aerial Vehicle Planning Methods Ontology

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