UAV obstacle avoidance by human-in-the-loop reinforcement in arbitrary 3D environment
This paper focuses on the continuous control of the unmanned aerial vehicle (UAV) based
on a deep reinforcement learning method for a large-scale 3D complex environment. The …
on a deep reinforcement learning method for a large-scale 3D complex environment. The …
[PDF][PDF] Deep Reinforcement Learning Based Unmanned Aerial Vehicle (UAV) Control Using 3D Hand Gestures.
The evident change in the design of the autopilot system produced massive help for the
aviation industry and it required frequent upgrades. Reinforcement learning delivers …
aviation industry and it required frequent upgrades. Reinforcement learning delivers …
Vehicle Detection and Counting for Traffic Congestion Estimation Using YOLOv5 and DeepSORT in Smart Traffic Light Application
MNH Mohd, YZ Kam, C Uttraphan… - Online Journal for …, 2024 - penerbit.uthm.edu.my
The escalating number of vehicles on the roads has exacerbated traffic congestion,
presenting a significant and inevitable challenge for road users. To address this issue, deep …
presenting a significant and inevitable challenge for road users. To address this issue, deep …
Benchmarking of an Enhanced Grasshopper for Feature Map Optimization of 3D and Depth Map Hand Gestures
Abstract The Enhanced Grasshopper Optimizer (EGO) for the feature map optimization of 3D
and depth map hand gestures is the objective of this paper's benchmarking experiment …
and depth map hand gestures is the objective of this paper's benchmarking experiment …
基于多智能体深度**化学**的无人机集群自主决策.
刘志飞， 曹雷， 赖俊， 陈希亮 - Information Technology & …, 2022 - search.ebscohost.com
Because the traditional UAV is controlled manually, UAV cluster is more rigid in the strong
electromagnetic interference and complex and changeable battlefield environment. In the …
electromagnetic interference and complex and changeable battlefield environment. In the …