Results 61 to 70 of about 4,069,375 (260)

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

Convolutional Graph Neural Networks

, 2019
Convolutional neural networks (CNNs) restrict the, otherwise arbitrary, linear operation of neural networks to be a convolution with a bank of learned filters.
Ribeiro, Alejandro (author), Gama, Fernando (author), Fernando Gama, Antonio G. Marques, Marques, Antonio G. (author), Alejandro Ribeiro, Geert Leus, Leus, G.J.T. (author)   +7 more
core   +1 more source

Understanding Pooling in Graph Neural Networks [PDF]

, 2021
Inspired by the conventional pooling layers in convolutional neural networks, many recent works in the field of graph machine learning have introduced pooling operators to reduce the size of graphs. The great variety in the literature stems from the many
Grattarola, Daniele, Zambon, Daniele, Daniele Zambon, Bianchi, Filippo Maria, Filippo Maria Bianchi, Alippi, Cesare, Cesare Alippi, Daniele Grattarola   +7 more
core   +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

Dynamic gesture recognition based on 2D convolutional neural network and feature fusion

Scientific Reports, 2022
Gesture recognition is one of the most popular techniques in the field of computer vision today. In recent years, many algorithms for gesture recognition have been proposed, but most of them do not have a good balance between recognition efficiency and ...
Jimin Yu, Maowei Qin, Shangbo Zhou
doaj   +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

Graph Neural Networks: A Bibliometric Mapping of the Research Landscape and Applications

Information
Graph neural networks (GNNs) are deep learning algorithms that process graph-structured data and are suitable for applications such as social networks, physical models, financial markets, and molecular predictions.
Annielle Mendes Brito da Silva, Natiele Carla da Silva Ferreira, Luiza Amara Maciel Braga, Fabio Batista Mota, Victor Maricato, Luiz Anastacio Alves   +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

Petrographic analysis with deep convolutional neural networks [PDF]

, 2019
Petrographic analysis is based on the microscopic description and classification of rocks and is a crucial technique for sedimentary and diagenetic studies.
Pires de Lima, Rafael
core  

Sample and Aggregate Voronoi Neighborhood Weighted Graph Neural Network (SAGE-Voronoi) and Its Capability for City-Sized Vehicle Traffic Time Series Prediction

Applied Sciences
The application of graph convolutional neural networks for traffic prediction is a standard procedure; however, this approach is rarely used under the assumption that the exact city plan is unknown and the prediction area is a city-sized region.
Przemysław Bielecki, Tomasz Hachaj, Jarosław Wąs   +2 more
doaj   +1 more source