A review of cooperative path planning of an unmanned aerial vehicle group

Zhang, Hao; Xin, Bin; Dou, Lihua; Chen, Jie; Hirota, Kaoru

doi:10.1631/fitee.2000228

Cited by 65 publications

(29 citation statements)

References 106 publications

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“…To simplify the search decision, a UAV is regarded as a particle in space. e task area is divided into a W × H grid map where the two-dimensional coordinates (w, h) are used to discretize the UAV motion range and decision set [25]. Assuming that the UAV moves in the grid every time, the constraint of normal overload of UAV movement is satisfied by limiting the grid size and the maximum turning angle, thus ensuring flyability along the planned track.…”

Section: Uav Motion Modelmentioning

confidence: 99%

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Cooperative Target Search of UAV Swarm with Communication Distance Constraint

Wang

Liang

et al. 2021

Mathematical Problems in Engineering

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This paper proposes a cooperative search algorithm to enable swarms of unmanned aerial vehicles (UAVs) to capture moving targets. It is based on prior information and target probability constrained by inter-UAV distance for safety and communication. First, a rasterized environmental cognitive map is created to characterize the task area. Second, based on Bayesian theory, the posterior probability of a target’s existence is updated using UAV detection information. Third, the predicted probability distribution of the dynamic time-sensitive target is obtained by calculating the target transition probability. Fourth, a customized information interaction mechanism switches the interaction strategy and content according to the communication distance to produce cooperative decision-making in the UAV swarm. Finally, rolling-time domain optimization generates interactive information, so interactive behavior and autonomous decision-making among the swarm members are realized. Simulation results showed that the proposed algorithm can effectively complete a cooperative moving-target search when constrained by communication distance yet still cooperate effectively in unexpected situations such as a fire.

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Section: Uav Motion Modelmentioning

confidence: 99%

“…Step 3: information interaction. When the UAV reaches the communication range of the other members of the swarm, the interactive information of the other members is fused by formula (25), and the cognitive map of its own decision environment is updated.…”

Section: Algorithm Flowmentioning

confidence: 99%

Cooperative Target Search of UAV Swarm with Communication Distance Constraint

Wang

Liang

et al. 2021

Mathematical Problems in Engineering

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“…Furthermore, previous studies focused on developing the autonomy and authority of the vehicle, thereby inadvertently degrading the driver's role and importance. In the future, next-generation autonomous vehicles should be more intelligent, safe, and personalized [60][61][62][63][64][65][66][67][68][69]. Therefore, the relationship between the driver and vehicle should be discussed further to support the research and development (R&D) of the futuristic automated vehicle.…”

Section: Introductionmentioning

confidence: 99%

Review and Perspectives on Driver Digital Twin and Its Enabling Technologies for Intelligent Vehicles

Lou

Xing

et al. 2022

IEEE Trans. Intell. Veh.

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Digital Twin (DT) is an emerging technology and has been introduced into intelligent driving and transportation systems to digitize and synergize connected automated vehicles. However, existing studies focus on the design of the automated vehicle, whereas the digitization of the human driver, who plays an important role in driving, is largely ignored. Furthermore, previous driver-related tasks are limited to specific scenarios and have limited applicability. Thus, a novel concept of a driver digital twin (DDT) is proposed in this study to bridge the gap between existing automated driving systems and fully digitized ones and aid in the development of a complete driving human cyber-physical system (H-CPS). This concept is essential for constructing a harmonious human-centric intelligent driving system that considers the proactivity and sensitivity of the human driver. The primary characteristics of the DDT include multimodal state fusion, personalized modeling, and time variance. Compared with the original DT, the proposed DDT emphasizes on internal personality and capability with respect to the external physiological-level state. This study systematically illustrates the DDT and outlines its key enabling aspects. The related technologies are comprehensively reviewed and discussed with a view to improving them by leveraging the DDT. In addition, the potential applications and unsettled challenges are considered. This study aims to provide fundamental theoretical support to researchers in determining the future scope of the DDT system.

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“…F OREST fire is one of the most destructive disasters to the ecological environment, and the forest fire protection is receiving more and more attention from the governments of the world [1]. Thus, it is very meaningful to carry out prevention and control of the forest fire, and how to make use of high-tech means to monitor forest fire has become a hot topic [2], [3].…”

Section: Introductionmentioning

confidence: 99%

Data Collection Task Planning of a Fixed-Wing Unmanned Aerial Vehicle in Forest Fire Monitoring

et al. 2021

Self Cite

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This article studies the data collection task planning for a fixed-wing unmanned aerial vehicle (UAV) in forest fire monitoring. Multiple wireless-based detection nodes (DNs) are distributed in highrisk areas of the forest to monitor the surrounding environment. The task of UAV is to circularly fly to them and collect the environmental data. Because of the kinematic constraints of UAV and the effective communication range between UAV and DN, this problem can be generally regarded as a Dubins traveling salesman problem with neighborhood (DTSPN). A bi-level hybridization-based metaheuristic algorithm (BLHMA) is proposed for solving this problem. At the first level, differential evolution (DE) optimizes the continuous-valued communication positions and UAV headings by the population-based search. For the asymmetric traveling salesman problem (ATSP) corresponding to the combination of the positions and headings generated by DE, a constructive heuristic based on self-organized multi-agent competition (SOMAC) is proposed to determine the discrete collection sequence. By competitive iterations in such a cooperative way in DE, a high-quality data collection tour can be generated. At the second level, a local search based on multistage approximate gradient is proposed to further refine the positions and headings, which accelerates the convergence of the BLHMA. Referring to a real-world scene of forest fire mornitoring, the simulation experiments are designed, and comparative results show that BLHMA can find significantly shorter data collection tours in most cases over three state-of-the-art algorithms. The proposed UAV data collection planning algorithm is conducive to the efficient execution of the forest fire monitoring data collection mission and the energy saving of UAV.

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A review of cooperative path planning of an unmanned aerial vehicle group

Cited by 65 publications

References 106 publications

Cooperative Target Search of UAV Swarm with Communication Distance Constraint

Cooperative Target Search of UAV Swarm with Communication Distance Constraint

Review and Perspectives on Driver Digital Twin and Its Enabling Technologies for Intelligent Vehicles

Data Collection Task Planning of a Fixed-Wing Unmanned Aerial Vehicle in Forest Fire Monitoring

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