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Wanlu Zhu, Tianwen Gu, Jie Wu and Zhengzhuo Liang
In instances where vessels encounter impacts or other factors leading to communication impairments, the status of electrical equipment becomes inaccessible through standard communication lines for the controllers. Consequently, the shipboard power system...
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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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Juri Hinz
In industrial applications, the processes of optimal sequential decision making are naturally formulated and optimized within a standard setting of Markov decision theory. In practice, however, decisions must be made under incomplete and uncertain inform...
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Angeliki Zacharaki, Ioannis Kostavelis and Ioannis Dokas
During the last decades, collaborative robots capable of operating out of their cages are widely used in industry to assist humans in mundane and harsh manufacturing tasks. Although such robots are inherently safe by design, they are commonly accompanied...
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Junjie Zeng, Long Qin, Yue Hu, Quanjun Yin and Cong Hu
Since an individual approach can hardly navigate robots through complex environments, we present a novel two-level hierarchical framework called JPS-IA3C (Jump Point Search improved Asynchronous Advantage Actor-Critic) in this paper for robot navigation ...
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