Results 81 to 90 of about 3,278,052 (298)

Data‐Driven Bulldozer Blade Control for Autonomous Terrain Leveling

Advanced Robotics Research, EarlyView.
A simulation‐driven framework for autonomous bulldozer leveling is presented, combining high‐fidelity terramechanics simulation with a neural‐network‐based reduced‐order model. Gradient‐based optimization enables efficient, low‐level blade control that balances leveling quality and operation time.
Harry Zhang, Ganesh Arivoli, Huzaifa Unjhawala, Luning Bakke, Radu Serban, Dan Negrut   +5 more
wiley   +1 more source

Intelligent Maintenance Review for Robots: Multimodal Information, Deep Diagnosis and Embodied Artificial Intelligence

Advanced Robotics Research, EarlyView.
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao, Hongbo Wang, Naipeng Li, Shuo Wang, Yaguo Lei, Tonghai Wu, Junyi Cao   +6 more
wiley   +1 more source

Graph convolutional networks for student answers assessment

, 2020
Graph Convolutional Networks have achieved impressive results in multiple NLP tasks such as text classification. However, this approach has not been explored yet for the student answer assessment task.
Rus, Vasile, Ait Khayi, Nisrine
core   +1 more source

Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges

Advanced Robotics Research, EarlyView.
This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder, Jelizaveta Konstantinova, Graham Deacon, Kaspar Althoefer   +3 more
wiley   +1 more source

Utilizing correlation in space and time: Anomaly detection for Industrial Internet of Things (IIoT) via spatiotemporal gated graph attention network

Alexandria Engineering Journal
The Industrial Internet of Things (IIoT) infrastructure is inherently complex, often involving a multitude of sensors and devices. Ensuring the secure operation and maintenance of these systems is increasingly critical, making anomaly detection a vital ...
Yuxin Fan, Tingting Fu, Nikolai Izmailovich Listopad, Peng Liu, Sahil Garg, Mohammad Mehedi Hassan   +5 more
doaj   +1 more source

CoLM2S: Contrastive self‐supervised learning on attributed multiplex graph network with multi‐scale information

CAAI Transactions on Intelligence Technology, 2023
Contrastive self‐supervised representation learning on attributed graph networks with Graph Neural Networks has attracted considerable research interest recently. However, there are still two challenges.
Beibei Han, Yingmei Wei, Qingyong Wang, Shanshan Wan   +3 more
doaj   +1 more source

Adaptive Graph-Learning Convolutional Network for Multi-Node Offshore Wind Speed Forecasting

Journal of Marine Science and Engineering, 2023
Multi-node wind speed forecasting is greatly important for offshore wind power. It is a challenging task due to unknown complex spatial dependencies. Recently, graph neural networks (GNN) have been applied to wind forecasting because of their capability ...
Jingjing Liu, Xinli Yang, Denghui Zhang, Ping Xu, Zhuolin Li, Fengjun Hu   +5 more
doaj   +1 more source

Flexible Sensors for Robotics Tactile Perception: A Review

Advanced Robotics Research, EarlyView.
Flexible tactile sensing for robotics is reviewed through four interconnected dimensions. Physical mechanisms include piezoresistive, capacitive, piezoelectric, triboelectric, iontronic, and optical sensing. Structural design includes bioinspired, defect‐based, and MEMS‐based tactile systems.
Yu Song, Ying Chen, Yihao Chen, Xue Feng
wiley   +1 more source

Semi-Supervised Node Classification With Discriminable Squeeze Excitation Graph Convolutional Networks

IEEE Access, 2020
In recent years, Graph Convolutional Networks (GCNs) have been increasingly and widely used in graph data representation and semi-supervised learning. GCNs can reveal and dig deep into irregular data with spatial topological structure.
Nan Jia, Xiaolin Tian, Yang Zhang, Fengge Wang   +3 more
doaj   +1 more source

Atomic Defects in Layered Transition Metal Dichalcogenides for Sustainable Energy Storage and the Intelligent Trends in Data Analytics

Advanced Science, EarlyView.
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo, Ying Yang, Zizhen Fu, Fengqi Liu, Susu Fang, Kele Xu, Shanshan Wang   +6 more
wiley   +1 more source