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Jiacun Wang, Guipeng Xi, Xiwang Guo, Shujin Qin and Henry Han
The scheduling of disassembly lines is of great importance to achieve optimized productivity. In this paper, we address the Hybrid Disassembly Line Balancing Problem that combines linear disassembly lines and U-shaped disassembly lines, considering multi...
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Xiaoyong Zhang, Wei Yue and Wenbin Tang
To enhance the anti-submarine and search capabilities of multiple Unmanned Aerial Vehicle (UAV) groups in complex marine environments, this paper proposes a flexible action-evaluation algorithm known as Knowledge-Driven Soft Actor-Critic (KD-SAC), which ...
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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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Yue Wang, Kexv Li, Xing Zhuang, Xinyu Liu and Hanyu Li
The penetration of unmanned aerial vehicles (UAVs) is an important aspect of UAV games. In recent years, UAV penetration has generally been solved using artificial intelligence methods such as reinforcement learning. However, the high sample demand of th...
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Minseok Kong and Jungmin So
There are several automated stock trading programs using reinforcement learning, one of which is an ensemble strategy. The main idea of the ensemble strategy is to train DRL agents and make an ensemble with three different actor?critic algorithms: Advant...
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Zhuo Wang, Hao Lu, Hongde Qin and Yancheng Sui
This study aims to solve the issue of the safe navigation of autonomous underwater vehicles (AUVs) in an unknown underwater environment. AUV will encounter canyons, rocks, reefs, fish, and underwater vehicles that threaten its safety during underwater na...
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Marta Ribeiro, Joost Ellerbroek and Jacco Hoekstra
Future operations involving drones are expected to result in traffic densities that are orders of magnitude higher than any observed in manned aviation. Current geometric conflict resolution (CR) methods have proven to be very efficient at relatively mod...
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Marta Ribeiro, Joost Ellerbroek and Jacco Hoekstra
Future high traffic densities with drone operations are expected to exceed the number of aircraft that current air traffic control procedures can control simultaneously. Despite extensive research on geometric CR methods, at higher densities, their perfo...
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Honghu Xue, Benedikt Hein, Mohamed Bakr, Georg Schildbach, Bengt Abel and Elmar Rueckert
We propose a deep reinforcement learning approach for solving a mapless navigation problem in warehouse scenarios. In our approach, an automatic guided vehicle is equipped with two LiDAR sensors and one frontal RGB camera and learns to perform a targeted...
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Zhihan Xue and Tad Gonsalves
Research on autonomous obstacle avoidance of drones has recently received widespread attention from researchers. Among them, an increasing number of researchers are using machine learning to train drones. These studies typically adopt supervised learning...
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