Results 111 to 120 of about 232,443 (272)

Compilation of training datasets for use of convolutional neural networks supporting automatic inspection processes in industry 4.0 based electronic manufacturing [PDF]

, 2020
Alida Ilse Maria Schwebig, Rainer Tutsch
openalex   +1 more source

Integration of Soft‐Robotics and Deep Learning to Assess the Coordinated Biosonar Emission and Reception Dynamics in Hipposiderid Bats

Advanced Robotics Research, EarlyView.
Combining a biomimetic soft‐robot with deep‐learning data analytics sheds light on a unique peripheral dynamics seen in the biosonar system of bats: Bats modulate their ultrasonic biosonar signals upon emission as well as reception with variable, yet highly coordinated motion patterns of their noseleaves and pinnae.
Shuxin Zhang, Ruihao Wang, Xiaoyan Yin, Luhui Yang, Rolf Müller   +4 more
wiley   +1 more source

Application of deep learning for division of petroleum reservoirs

MATEC Web of Conferences, 2018
Traditional methods of dividing petroleum reservoirs are inefficient, and the accuracy of onehidden-layer BP neural network is not ideal when applied to dividing reservoirs.
Qin Yaqiong, Ye Zhaohui, Zhang Conghui
doaj   +1 more source

Flexible Sensor‐Based Human–Machine Interfaces with AI Integration for Medical Robotics

Advanced Robotics Research, EarlyView.
This review explores how flexible sensing technology and artificial intelligence (AI) significantly enhance human–machine interfaces in medical robotics. It highlights key sensing mechanisms, AI‐driven advancements, and applications in prosthetics, exoskeletons, and surgical robotics.
Yuxiao Wang, Zhipeng Jiang, Sun Hwa Kwon, Matthew Ibrahim, Alexander Dang, Lin Dong   +5 more
wiley   +1 more source

3D Elastomeric Kirigami for Passively Stretchable Fully Soft Vacuum‐Powered Artificial Muscles

Advanced Robotics Research, EarlyView.
The creation of purely soft, passively stretchable artificial muscles has long been a hot topic in robotics research. Here, we present a design approach involving the extension of 2D kirigami to 3D elastomeric kirigami structures. In a biomimetic demonstration of the human upper arm, this approach successfully simulated the driving mechanism ...
Tao Wang, Hongyuan Wang, Qian Liu, Xi Wang, Guoqiang Fu, Caijiang Lu, Bo Li, Jinhua Zhang, Hongying Zhang   +8 more
wiley   +1 more source

Liquid Metal Sensors for Soft Robots

Advanced Robotics Research, EarlyView.
This review thoroughly reviews liquid metal sensors in soft robots. Their unique material properties like high conductivity and good biocompatibility are analyzed. Working principles are classified, and applications in environmental perception, motion detection, and human—robot interaction are introduced.
Qi Zhang, Nan Li, Yujia Song, Chen Hua, Tangzhen Guan, Yibing Ma, Cai Cheng, Jing Liu   +7 more
wiley   +1 more source

Modelling of energy productivity prediction systems of shallots classification growth phase system using convolutional neural network

, 2023
Riswanti Sigalingging, Stefanni Nababan, Noverita Sprinse Vinolina, Lukman Adlin Harahap   +3 more
openalex   +1 more source

Retracted: Empirical Analysis of Financial Depth and Width Based on Convolutional Neural Network [PDF]

, 2023
Computational Intelligence and Neuroscience
openalex   +1 more source

An AI‐Enabled All‐In‐One Visual, Proximity, and Tactile Perception Multimodal Sensor

Advanced Robotics Research, EarlyView.
Targeting integrated multimodal perception of robots, an AI‐enabled all‐in‐one multimodal sensor is proposed. This sensor is capable of perceiving three types of modalities, including vision, proximity, and tactility. By toggling an ultraviolet light and adjusting the camera focus, it switches smoothly between multiple perceptual modalities, enabling ...
Menghao Pu, Tiyong Zhao, Lingxi Zhang, Chaoqun Han, Zhiping Chai, Yifan Zhou, Han Ding, Zhigang Wu   +7 more
wiley   +1 more source

The Future of Research in Cognitive Robotics: Foundation Models or Developmental Cognitive Models?

Advanced Robotics Research, EarlyView.
Research in cognitive robotics founded on principles of developmental psychology and enactive cognitive science would yield what we seek in autonomous robots: the ability to perceive its environment, learn from experience, anticipate the outcome of events, act to pursue goals, and adapt to changing circumstances without resorting to training with ...
David Vernon
wiley   +1 more source