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Zixiao Zhu, Lichuan Zhang, Lu Liu, Dongwei Wu, Shuchang Bai, Ranzhen Ren and Wenlong Geng
Positioning errors introduced by low-precision navigation devices can affect the overall accuracy of a positioning system. To address this issue, this paper proposes a master-slave multi-AUV collaborative navigation method based on hierarchical reinforce...
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Shaowei Li, Yongchao Wang, Yaoming Zhou, Yuhong Jia, Hanyue Shi, Fan Yang and Chaoyue Zhang
Multiple unmanned aerial vehicle (multi-UAV) cooperative air combat, which is an important form of future air combat, has high requirements for the autonomy and cooperation of unmanned aerial vehicles. Therefore, it is of great significance to study the ...
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Shuai Liu, Jing He and Jiayun Wu
Dynamic spectrum access (DSA) has been considered as a promising technology to address spectrum scarcity and improve spectrum utilization. Normally, the channels are related to each other. Meanwhile, collisions will be inevitably caused by communicating ...
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Wei Yue, Xianhe Guan and Liyuan Wang
In this paper, the important topic of cooperative searches for multi-dynamic targets in unknown sea areas by unmanned aerial vehicles (UAVs) is studied based on a reinforcement learning (RL) algorithm. A novel multi-UAV sea area search map is established...
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Muhidul Islam Khan, Muhammad Mahtab Alam, Yannick Le Moullec and Elias Yaacoub
Device-to-device (D2D) communication is an essential feature for the future cellular networks as it increases spectrum efficiency by reusing resources between cellular and D2D users. However, the performance of the overall system can degrade if there is ...
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Muhidul Islam Khan, Muhammad Mahtab Alam, Yannick Le Moullec and Elias Yaacoub
Device-to-device (D2D) communication is an essential feature for the future cellular networks as it increases spectrum efficiency by reusing resources between cellular and D2D users. However, the performance of the overall system can degrade if there is ...
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Angelo Borneo, Luca Zerbato, Federico Miretti, Antonio Tota, Enrico Galvagno and Daniela Anna Misul
In recent decades, the automotive industry has moved towards the development of advanced driver assistance systems to enhance the comfort, safety, and energy saving of road vehicles. The increasing connection and communication between vehicles (V2V) and ...
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Chen Chen, Feng Ma, Xiaobin Xu, Yuwang Chen and Jin Wang
Ships are special machineries with large inertias and relatively weak driving forces. Simulating the manual operations of manipulating ships with artificial intelligence (AI) and machine learning techniques becomes more and more common, in which avoiding...
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Yoshinari Motokawa and Toshiharu Sugawara
In this paper, we propose an enhanced version of the distributed attentional actor architecture (eDA3-X) for model-free reinforcement learning. This architecture is designed to facilitate the interpretability of learned coordinated behaviors in multi-age...
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Yu Chen, Qi Dong, Xiaozhou Shang, Zhenyu Wu and Jinyu Wang
Unmanned aerial vehicles (UAVs) are important in reconnaissance missions because of their flexibility and convenience. Vitally, UAVs are capable of autonomous navigation, which means they can be used to plan safe paths to target positions in dangerous su...
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James Blaise and Michael C. F. Bazzocchi
Recent efforts in on-orbit servicing, manufacturing, and debris removal have accentuated some of the challenges related to close-proximity space manipulation. Orbital debris threatens future space endeavors driving active removal missions. Additionally, ...
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Beipo Su, Yongfeng Ju and Liang Dai
Video application is a research hotspot in cooperative vehicle-infrastructure systems (CVIS) which is greatly related to traffic safety and the quality of user experience. Dealing with large datasets of feedback from complex environments is a challenge w...
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Yuzhu Zhang and Hao Xu
This study investigates the problem of decentralized dynamic resource allocation optimization for ad-hoc network communication with the support of reconfigurable intelligent surfaces (RIS), leveraging a reinforcement learning framework. In the present co...
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Jishu K. Medhi, Rui Liu, Qianlong Wang and Xuhui Chen
Multiple unmanned aerial vehicle (multi-UAV) systems have gained significant attention in applications, such as aerial surveillance and search and rescue missions. With the recent development of state-of-the-art multiagent reinforcement learning (MARL) a...
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Naifeng Wen, Yundong Long, Rubo Zhang, Guanqun Liu, Wenjie Wan and Dian Jiao
This research introduces a two-stage deep reinforcement learning approach for the cooperative path planning of unmanned surface vehicles (USVs). The method is designed to address cooperative collision-avoidance path planning while adhering to the Interna...
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Giorgos Mitsis, Pavlos Athanasios Apostolopoulos, Eirini Eleni Tsiropoulou and Symeon Papavassiliou
Software Defined Networks (SDN) and Mobile Edge Computing (MEC), capable of dynamically managing and satisfying the end-users computing demands, have emerged as key enabling technologies of 5G networks. In this paper, the joint problem of MEC server sele...
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Chenglong Li, Wenyong Gu, Yuan Zheng, Longyang Huang and Xuejun Zhang
Air logistics transportation has become one of the most promising markets for the civil drone industry. However, the large flow, high density, and complex environmental characteristics of urban scenes make tactical conflict resolution very challenging. E...
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Yazhi Liu, Dongyu Wei, Chunyang Zhang and Wei Li
In QoE fairness optimization of multiple video streams, a distributed video stream fairness scheduling strategy based on federated deep reinforcement learning is designed to address the problem of low bandwidth utilization due to unfair bandwidth allocat...
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Xiaoxiong Liu, Yi Yin, Yuzhan Su and Ruichen Ming
To solve the problems of autonomous decision making and the cooperative operation of multiple unmanned combat aerial vehicles (UCAVs) in beyond-visual-range air combat, this paper proposes an air combat decision-making method that is based on a multi-age...
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Eirini Eleni Tsiropoulou, George Kousis, Athina Thanou, Ioanna Lykourentzou and Symeon Papavassiliou
This paper addresses the problem of museum visitors? Quality of Experience (QoE) optimization by viewing and treating the museum environment as a cyber-physical social system. To achieve this goal, we harness visitors? internal ability to intelligently s...
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