Adaptive Quantized Control Research for Hysteresis Nonlinear Systems in Piezoelectric Positioning Stages Background Introduction In modern high-precision positioning systems, smart materials (such as piezoelectric ceramics) are widely used in micro/nano manufacturing and soft robotics due to their excellent performance. However, the inherent hyster...

Modular Brain-Machine Interface: Innovative Breakthrough in Neurorecording, Neurostimulation, and Drug Delivery Academic Background Brain-Machine Interfaces (BMIs) are crucial tools in neuroscience and clinical medicine, enabling interactions between the brain and the external world through charge, matter, and information exchange. They are widely ...

Research on an Ultra-Low Power Carbon Dioxide Sensor for Real-Time Breath Monitoring Academic Background Carbon dioxide (CO₂) is a critical gas produced during human respiration, and its real-time monitoring is essential for diagnosing and treating respiratory diseases (e.g., asthma, dyspnea, sleep apnea) as well as metabolic disorders. Traditional...

Research on Multi-material Biomimetic Electronics Based on Investment Micro-casting 3D Printing Academic Background With the rapid development of biomimetic electronics, electronic skin (E-skin) and flexible sensors that mimic human perceptual functions have shown broad application prospects in robotics, medical devices, and human-computer interact...

Sweat Fingerprint Identification Technology Based on Ion Dynamics: Research on Inkjet-Printed Organic Electrochemical Transistor Arrays Academic Background Sweat, as a non-invasive biomarker, contains rich physiological information that can reflect human health conditions, such as hydration balance and disease markers. However, sweat has complex co...

Floating Omnidirectional Droplet Vibration Generator: Breakthrough Research Academic Background With the widespread application of Internet of Things (IoT) devices in marine environmental monitoring, how to provide stable power to these devices without relying on the power grid has become an urgent issue. Traditional renewable energy sources such a...

With the rapid development of artificial intelligence (AI) technologies, deep learning has made significant progress in complex tasks. However, the success of deep learning largely relies on massive amounts of labeled data, and the data labeling process is not only time-consuming and labor-intensive but also requires specialized domain knowledge, m...

Multi-agent Cooperative Navigation in Hybrid Environments: A New Reinforcement Learning Approach Based on Relational Graph Learning Mobile robotics is witnessing a surge in applications, fueled by advancements in artificial intelligence, with navigation capabilities being one of the core focus areas of research. Traditional navigation methods often...

Nonlinear Fixed-Time Reinforcement Learning Optimized Control for Intelligent Ship Autopilots In recent years, intelligent autopilot technology has gradually become a research hotspot in the field of automation control. For complex nonlinear systems, the design of optimized control strategies, especially the achievement of system stability and perf...

Policy Consensus-Based Distributed Deterministic Multi-Agent Reinforcement Learning Research Report Reinforcement Learning (RL) has made significant breakthroughs in recent years in various fields such as robotics, smart grids, and autonomous driving. However, in real-world scenarios, multi-agent collaboration problems, also known as Multi-Agent Re...