Results 91 to 100 of about 5,528,069 (258)

Data‐Driven Bulldozer Blade Control for Autonomous Terrain Leveling

open access: yesAdvanced 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   +5 more
wiley   +1 more source

Architecture of the Convolutional Neural Network.

open access: yes, 2018
Illustration of the convolutional neural network model utilizing word, position, part of speech and chunk embeddings.
Ganesh Bagler (119952)   +3 more
core   +1 more source

Cross‐Scale Hierarchical Targeted Delivery System Based on Small‐Scale Magnetic Robots

open access: yesAdvanced Robotics Research, EarlyView.
This article reviews a cross‐scale hierarchical targeted delivery system that integrates magnetic continuum robots and magnetic microrobots. By combining rapid long‐range navigation with precise microscale targeting, the system overcomes key limitations of single‐scale approaches.
Junjian Zhou   +4 more
wiley   +1 more source

Large receptive field convolutional neural network for image super-resolution

open access: yes, 2017
This paper presents a new approach to Single Image Super Resolution (SISR), based upon Convolutional Neural Network (CNN). Although the SISR is ill-posed which can be seen as finding a non-linear mapping from a low to high dimensional space.
Wang Q(王强)   +3 more
core  

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

open access: yesAdvanced 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   +6 more
wiley   +1 more source

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

open access: yesAdvanced 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   +3 more
wiley   +1 more source

Continuum Robots in Surgery: From Engineering Design to Clinical Practice

open access: yesAdvanced Robotics Research, EarlyView.
The hyper‐redundant nature of continuum robot structures enables near‐infinite degrees of freedom leading to immense potential for medical applications. This review provides a historical background of continuum robots and novel ideas shaping their progress to current structural design, sensing technology, modeling techniques, and control methods.
Griffin Smith   +6 more
wiley   +1 more source

Learning shape correspondence with anisotropic convolutional neural networks [PDF]

open access: yes, 2016
Convolutional neural networks have achieved extraordinary results in many computer vision and pattern recognition applications; however, their adoption in the computer graphics and geometry processing communities is limited due to the non-Euclidean ...
Rodolà, Emanuele   +4 more
core  

Flexible Sensors for Robotics Tactile Perception: A Review

open access: yesAdvanced 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

A convolutional neural network for automatic analysis of aerial imagery [PDF]

open access: yes, 2014
This paper introduces a new method to automate the detection of marine species in aerial imagery using a Machine Learning approach. Our proposed system has at its core, a convolutional neural network. We compare this trainable classifier to a handcrafted
Amanda Hodgson   +8 more
core   +1 more source

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