Learning for a robot: Deep reinforcement learning, imitation learning, transfer learning
J Hua, L Zeng, G Li, Z Ju - Sensors, 2021 - mdpi.com
Dexterous manipulation of the robot is an important part of realizing intelligence, but
manipulators can only perform simple tasks such as sorting and packing in a structured …
manipulators can only perform simple tasks such as sorting and packing in a structured …
Lifetime prediction using a tribology-aware, deep learning-based digital twin of ball bearing-like tribosystems in oil and gas
PS Desai, V Granja, CF Higgs III - Processes, 2021 - mdpi.com
The recent decline in crude oil prices due to global competition and COVID-19-related
demand issues has highlighted the need for the efficient operation of an oil and gas plant …
demand issues has highlighted the need for the efficient operation of an oil and gas plant …
Deep reinforcement learning for the computation offloading in MIMO-based Edge Computing
Abstract Multi-access Edge Computing (MEC) has recently emerged as a potential
technology to serve the needs of mobile devices (MDs) in 5G and 6G cellular networks. By …
technology to serve the needs of mobile devices (MDs) in 5G and 6G cellular networks. By …
Weakly supervised reinforcement learning for autonomous highway driving via virtual safety cages
The use of neural networks and reinforcement learning has become increasingly popular in
autonomous vehicle control. However, the opaqueness of the resulting control policies …
autonomous vehicle control. However, the opaqueness of the resulting control policies …
A conceptual multi-layer framework for the detection of nighttime pedestrian in autonomous vehicles using deep reinforcement learning
The major challenge faced by autonomous vehicles today is driving through busy roads
without getting into an accident, especially with a pedestrian. To avoid collision with …
without getting into an accident, especially with a pedestrian. To avoid collision with …
Reinforcement learning for the face support pressure of tunnel boring machines
In tunnel excavation with boring machines, the tunnel face is supported to avoid collapse
and minimise settlement. This article proposes the use of reinforcement learning, specifically …
and minimise settlement. This article proposes the use of reinforcement learning, specifically …
Towards robust decision-making for autonomous highway driving based on safe reinforcement learning
R Zhao, Z Chen, Y Fan, Y Li, F Gao - Sensors, 2024 - mdpi.com
Reinforcement Learning (RL) methods are regarded as effective for designing autonomous
driving policies. However, even when RL policies are trained to convergence, ensuring their …
driving policies. However, even when RL policies are trained to convergence, ensuring their …
A reinforcement learning benchmark for autonomous driving in intersection scenarios
In recent years, control under urban intersection scenarios has become an emerging
research topic. In such scenarios, the autonomous vehicle confronts complicated situations …
research topic. In such scenarios, the autonomous vehicle confronts complicated situations …