|
|
|
|
|
Linfei Hou, Honglin Liu, Ting Yang, Shuaibin An and Rui Wang
In addressing the morphing problem in vehicle flight, some scholars have primarily employed reinforcement learning methods to make morphing decisions based on task. However, they have not considered the constraints associated with the task process. The i...
ver más
|
|
|
|
|
|
|
|
|
Jianping Yuan, Yingying She, Yinghao Zhang, Jun Xu and Lei Wan
This study focuses on addressing the the coupling problem of the vertical and horizontal plane of an autonomous underwater vehicle (AUV) with an X-rudder. To guarantee the steering performance of the AUV, a depth and course control algorithm based on an ...
ver más
|
|
|
|
|
|
|
|
|
Jibo Liu, Xiaoyu Liu, Xieyu Lv, Bo Wang and Xugang Lian
Addressing the problem that traditional methods cannot reliably monitor surface subsidence in coal mining, a novel method has been developed for monitoring subsidence in mining areas using time series unmanned aerial vehicle (UAV) photogrammetry in combi...
ver más
|
|
|
|
|
|
|
|
|
Martin Holen, Kristian Muri Knausgård and Morten Goodwin
Autonomous driving is a research field that has received attention in recent years, with increasing applications of reinforcement learning (RL) algorithms. It is impractical to train an autonomous vehicle thoroughly in the physical space, i.e., the so-ca...
ver más
|
|
|
|
|
|
|
|
|
Duy Quang Tran and Sang-Hoon Bae
Advanced deep reinforcement learning shows promise as an approach to addressing continuous control tasks, especially in mixed-autonomy traffic. In this study, we present a deep reinforcement-learning-based model that considers the effectiveness of leadin...
ver más
|
|
|
|