An Electroencephalogram Microdisplay to Visualize Neuronal Activity on the Brain Surface

An Electroencephalogram Microdisplay to Visualize Neuronal Activity on the Brain Surface

A Visualization Microdisplay for Neuronal Activity on the Brain Surface Using Electroencephalography Background Introduction Current functional mapping in neurosurgery primarily relies on verbal communication between neurosurgeons and electrophysiologists. These processes are time-consuming and have limited resolution. Additionally, the electrode g...

Fully Neuromorphic Vision and Control for Autonomous Drone Flight

Fully Neuromorphic Vision and Control for Autonomous Drone Flight

Fully Neuromorphic Visual and Control Autonomous Aerial Vehicle Background and Research Motivation Over the past decade, deep artificial neural networks (ANNs) have made significant advancements in the field of artificial intelligence, particularly in visual processing. However, these advanced visual processing technologies, despite achieving high ...

Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning

Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning

Deep Reinforcement Learning Empowers Agile Soccer Skills for Bipedal Robots Background Introduction One of the long-term goals of artificial intelligence (AI) research is to enable agents to exhibit agility, flexibility, and understanding in the physical world. However, animals and humans not only smoothly complete complex physical actions but also...

Learning Robust Autonomous Navigation and Locomotion for Wheeled-Legged Robots

Learning Robust Autonomous Navigation and Locomotion for Wheeled-Legged Robots

Autonomous Navigation and Walking Wheel-Leg Robot Background Introduction The acceleration of urbanization has posed significant challenges for supply chain logistics, especially for last-mile delivery. As traffic pressure increases and the demand for faster delivery services rises, particularly with complex routes indoors and on city streets, trad...

Stereoscopic Artificial Compound Eyes for Spatiotemporal Perception in Three-Dimensional Space

Stereoscopic Artificial Compound Eyes for Spatiotemporal Perception in Three-Dimensional Space

Stereoscopic Artificial Compound Eyes for Spatiotemporal Perception in Three-Dimensional Space This research article was published on May 15, 2024, in the journal Science Robotics, titled “Stereoscopic Artificial Compound Eyes for Spatiotemporal Perception in Three-Dimensional Space.” The first author is Byungjoon Bae, and the corresponding author ...

Real-World Humanoid Locomotion with Reinforcement Learning

Real-World Humanoid Locomotion with Reinforcement Learning

Real-World Humanoid Robot Walking Based on Reinforcement Learning Background Introduction Humanoid robots have enormous potential for autonomous operation in diverse environments, not only alleviating labor shortages in factories but also assisting elderly people at home and exploring new planets. Although classical controllers show excellent effec...

An Ultrawide Field-of-View Pinhole Compound Eye Using Hemispherical Nanowire Array for Robot Vision

An Ultrawide Field-of-View Pinhole Compound Eye Using Hemispherical Nanowire Array for Robot Vision

Ultra-wide Field-of-view Pinhole Compound Eye Based on Hemispherical Nanowire Array for Robotic Vision In the rapid development of contemporary artificial intelligence and robotics technology, the visual system, as a crucial component, has attracted widespread attention and in-depth research. According to a research paper published by Zhou et al. o...

Multi-Template Meta-Information Regularized Network for Alzheimer’s Disease Diagnosis Using Structural MRI

Multi-Template Meta-Information Regularized Network for Alzheimer’s Disease Diagnosis Using Structural MRI

Multi-template Meta-information Regularized Network for Alzheimer’s Disease Diagnosis: A Study Based on Structural MRI Research Background Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder, and its diagnosis and early detection is a significant challenge in the medical field. Structural MRI (sMRI) is widely used in computer-aided...

Noise-Generating and Imaging Mechanism Inspired Implicit Regularization Learning Network for Low Dose CT Reconstruction

Noise-Generating and Imaging Mechanism Inspired Implicit Regularization Learning Network for Low Dose CT Reconstruction

Application of Implicit Regularization Learning Network Based on Noise Generation and Imaging Mechanisms in Low-Dose CT Reconstruction Low-Dose Computed Tomography (LDCT) has become an important tool in modern medical imaging, aiming to reduce radiation risks while maintaining image quality. However, reducing the X-ray dose often leads to data corr...

Unsupervised Fusion of Misaligned PAT and MRI Images via Mutually Reinforcing Cross-Modality Image Generation and Registration

Unsupervised Fusion of Unaligned PAT and MRI Images Using Mutually Enhancing Cross-Modality Image Generation and Registration Methods Background and Research Objectives In recent years, photoacoustic tomography (PAT) and magnetic resonance imaging (MRI) have been widely used in preclinical research as cutting-edge biomedical imaging techniques. PAT...