Research Progress

• 07/21 -2026-
  New Dependency-Aware Method Enhances Information Freshness and Control in Industrial Systems

  To address this limitation, researchers from the Shenyang Institute of Automation (SIA) of the Chinese Academy of Sciences,developed a dependency-aware co-optimization method for sensing-transmission-computation-control (STCC) systems. The findings were published in IEEE Transactions on Mobile Computing.
• 07/15 -2026-
  Researchers Propose a Novel Algorithmic Framework for Large Model-Empowered Collaborative Optimization of Perception-Communication-Computation-Control

  ​Industrial Cyber-Physical Systems (ICPS) represent a quintessential deep coupling system integrating Sensing, Communication, Computation, and Control (S3C). They have long faced challenges such as high dimensionality, non-convexity, and partial observability. To address these challenges, the research team from Shenyang Institute of Automation(SIA) of Chinese Academy of Sciences, proposed a novel algorithmic framework: LLM-Enhanced Multi-Agent Transfer Reinforcement Learning (LLMPT-MADRL).
• 07/09 -2026-
  K2MUSE: Multimodal Walking Dataset Bri dges Lab-to-Real-World Gap for Rehabilitation Robots

  The ressearch team from the Shenyang Institute of Automation (SIA), Chinese Academy of Sciences, in collaboration with researchers from other universities, multiple university teams, has have released an open-source multimodal lower-limb walking dataset named K2MUSE.
• 07/09 -2026-
  New Wearable Microneedle Sensing Platform for Dopamine Detection Developed by SIABicatalytic Nanozyme Patch Enables Painless Dopamine Monitoring

  Recently, a research team from the Robotics Laboratory, Shenyang Institute of Automation (SIA) of the Chinese Academy of Sciences, has made progress in the field of wearable biosensing. Addressing the industrial bottleneck of achieving minimally invasive, real-time, highly sensitive, and accurate detection of dopamine in human skin interstitial fluid, the team innovatively constructed a wearable microneedle sensing platform integrated with a bicatalytic nanozyme, opening up a new technological pathway for dynamic neurotransmitter monitoring, early screening of neurological diseases, and home-based intelligent health monitoring.
• 07/06 -2026-
  A Statistically Informed Neural Network Enables Interpretable and Accurate Industrial Sensing Under Limited Data

  The realization of intelligent manufacturing in the process industry relies on real-time, accurate perception of key parameters during production. However, industrial sites commonly face challenges such as scarce labeled samples, strong noise interference, and complex nonlinear relationships. To address this issue, the LIBS team from the Industrial Control Network and System Department of the Shenyang Institute of Automation (SIA) of the Chinese Academy of Sciences, has proposed a partial least squares-assisted optimization network, termed PLSaoNET.
• 06/17 -2026-
  PAG-DAF: Power-Aware Graph Adaptation for SPND Fault Detection

  A research team from the Industrial Control Network and System Department at the Shenyang Institute of Automation (SIA), Chinese Academy of Sciences, has proposed a Power-Aware Graph Domain Adaptation Framework (PAG-DAF) tailored for variable power conditions.
• 05/25 -2026-
  Novel AI Method Enables Intelligent Reservoir Dynamic Simulation

  Recently, a research team from the Industrial Control Network and System Department of the Shenyang Institute of Automation (SIA) of the Chinese Academy of Sciences, proposed a novel method called PI-DeepOKAN, which deeply integrates physical laws with artificial intelligence, providing an efficient new tool for reservoir dynamic simulation and intelligent decision-making.
• 05/22 -2026-
  Digital Twin-Based High-Precision Docking Method Facilitating the Smart Manufacturing Upgrade of Aerospace Heavy Equipment 　　

  Recently, the Shenyang Institute of Automation (SIA) of the Chinese Academy of Sciences has made progress in the high-precision intelligent assembly of large-diameter cabin sections. The research team innovatively proposed a digital twin-driven virtual-physical collaborative assembly method, which provides a novel technical pathway for the intelligent assembly of heavy-duty aerospace equipment such as solid rocket motors.
• 05/22 -2026-
  New Integrated Fabrication and Joining Technique for CF/PEEK Composites Paves the Way for On-Orbit Construction of Large Space Structures 　　

  Recently, a research team from Shenyang Institute of Automation (SIA) of the Chinese Academy of Sciences, together with collaborators, have developed an integrated technique that combines pultrusion of carbon fiber/polyetheretherketone (CF/PEEK) composite tubular units with laser transmission welding, offering a lightweight, high-strength, and high-reliability solution for the automated on-orbit assembly of large space truss structures.
• 05/22 -2026-
  SIA Has Series of Research Papers Accepted by ICML 2026

  Recently, the Machine Intelligence Research Group at the Robotics Laboratory, Shenyang Institute of Automation (SIA) of the Chinese Academy of Sciences, has made important progress in robot imitation learning and polarization vision. A series of related research outcomes have been formally accepted by ICML 2026, a leading international conference in artificial intelligence.