[HTML][HTML] Deep Deterministic Policy Gradient Virtual Coupling control for the coordination and manoeuvring of heterogeneous uncertain nonlinear High-Speed Trains
The new railway mobility paradigm Virtual Coupling, recognized as one of the most
promising solutions to face the ever-increasing demand in railway transportation and the …
promising solutions to face the ever-increasing demand in railway transportation and the …
Achieving accurate trajectory predicting and tracking for autonomous vehicles via reinforcement learning-assisted control approaches
T Guangwen, L Mengshan, H Biyu, Z Jihong… - … Applications of Artificial …, 2024 - Elsevier
In complex urban traffic scenarios, autonomous vehicles face significant challenges in
adapting to diverse and dynamic traffic conditions. Reward-based reinforcement learning …
adapting to diverse and dynamic traffic conditions. Reward-based reinforcement learning …
Deep reinforcement learning and decoupling proportional-integral-derivative control of a humanoid cable-driven hybrid robot
Y Liu, Z Luo, S Qian, S Wang… - International Journal of …, 2024 - journals.sagepub.com
Aiming at the application of robots in service, medical treatment, rehabilitation, and other
fields, a humanoid cable-driven hybrid robot by imitating the structure of human arm is …
fields, a humanoid cable-driven hybrid robot by imitating the structure of human arm is …
Traversing Dynamic Environments: Advanced Deep Reinforcement Learning for Mobile Robots Path Planning-A Comprehensive Review
MH Qasim, S Al-Darraji - International Journal of Computing …, 2024 - journal.uob.edu.bh
Dynamic path planning involves finding the most efficient path between the beginning and
the destination in an unfamiliar and constantly changing environment while avoiding fixed …
the destination in an unfamiliar and constantly changing environment while avoiding fixed …
A path planning algorithm fusion of obstacle avoidance and memory functions
Q Zheng, S Li, P Zhu, W Ma… - … Computation and Systems, 2023 - Wiley Online Library
In this study, to address the issues of sluggish convergence and poor learning efficiency at
the initial stages of training, the authors improve and optimise the Deep Deterministic Policy …
the initial stages of training, the authors improve and optimise the Deep Deterministic Policy …