Function-dependent neural-network-driven state feedback control and self-verification stability for discrete-time nonlinear system
Deep learning significantly impacts neural network controller synthesis. Despite the higher
efficiency of deep learning algorithms compared to traditional model-based controller design …
efficiency of deep learning algorithms compared to traditional model-based controller design …
SIMPNet: Spatial-Informed Motion Planning Network
Current robotic manipulators require fast and efficient motion-planning algorithms to operate
in cluttered environments. State-of-the-art sampling-based motion planners struggle to scale …
in cluttered environments. State-of-the-art sampling-based motion planners struggle to scale …
Process Operating Performance Assessment for Plant-wide Froth Flotation via Distributed Multi-graph Deep Embedding Graph Clustering Network
D Lu, F Wang, Y Liu, S Wang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The process operating performance assessment (POPA) of the flotation process is of great
significance for monitoring the flotation operating performance and improving the product …
significance for monitoring the flotation operating performance and improving the product …
Transformer-Enhanced Motion Planner: Attention-Guided Sampling for State-Specific Decision Making
L Zhuang, J Zhao, Y Li, Z Xu, L Zhao, H Liu - arXiv preprint arXiv …, 2024 - arxiv.org
Sampling-based motion planning (SBMP) algorithms are renowned for their robust global
search capabilities. However, the inherent randomness in their sampling mechanisms often …
search capabilities. However, the inherent randomness in their sampling mechanisms often …