Results 81 to 90 of about 120,740 (217)
REWW‐ARM—Remote Wire‐Driven Mobile Robot: Design, Control, and Experimental Validation
The Remote Wire‐Driven robot “REWW‐ARM” demonstrates a new concept of remote actuation that separates electronics from harsh environments while retaining closed‐loop control. Combining tendon‐sheath mechanisms with decoupled joints, it achieves efficient power transmission and autonomous locomotion, manipulation, and underwater operation, suggesting ...
Takahiro Hattori +4 more
wiley +1 more source
This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi +3 more
wiley +1 more source
GraphNeuralCloth: A Graph‐Neural‐Network‐Based Framework for Non‐Skinning Cloth Simulation
This study presents a cloth motion capture system and a point‐cloud‐to‐mesh processing method to support the prediction of real‐world fabric deformation. GraphNeuralCloth, a graph neural‐network (GNN)‐based framework is also proposed to estimate the cloth morphology change in real time.
Yingqi Li +9 more
wiley +1 more source
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He +2 more
wiley +1 more source
Slip‐Adaptive Neural Control of Gecko‐Inspired Adhesive Robots
This study introduces a neural adhesion controller to improve the stability of gecko‐inspired climbing robots. By integrating an echo state network and a multilayer perceptron, the system utilizes joint torque feedback to accurately estimate adhesion in both normal and shear directions and predict slips. This enables effective recovery from slip events,
Donghao Shao +3 more
wiley +1 more source
TacEva: A Performance Evaluation Framework for Vision‐Based Tactile Sensors
This work introduces TacEva, a unified framework for evaluating vision‐based tactile sensors. It standardizes intrinsic, performance, and robustness metrics through shared experimental procedures and links them to task‐level requirements in robotic manipulation.
Qingzheng Cong +5 more
wiley +1 more source
Osmar Aléssio +4 more
semanticscholar +1 more source
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
Language‐Guided Robot Grasping Based on Basic Geometric Shape Fitting
This article presents a language‐guided, model‐free grasping framework that integrates multimodal perception with primitive‐based geometric fitting. By explicitly modeling object geometry from RGB‐D data, the method enables semantically controllable grasp pose generation and achieves robust performance in both structured and cluttered real‐world ...
Qun Niu +5 more
wiley +1 more source
Deep Learning Methods for Assessing Time‐Variant Nonlinear Signatures in Clutter Echoes
Motion classification from biosonar echoes in clutter presents a fundamental challenge: extracting structured information from stochastic interference. Deep learning successfully discriminates object speed and direction from bat‐inspired signals, achieving 97% accuracy with frequency‐modulated calls but only 48% with constant‐frequency tones. This work
Ibrahim Eshera +2 more
wiley +1 more source

