Research Progress

• 09/23 -2026-
  Plug-and-Play PNPTrack Boosts Visual Tracking Without Full Retraining

  A research team from the Opto-Electronic Information Technology Department of the Shenyang Institute of Automation(SIA), Chinese Academy of Sciences, has proposed a plug-and-play visual tracking framework named PNPTrack. This method effectively leverages spatiotemporal information to improve tracking stability and accuracy without requiring full-parameter retraining and without introducing additional spatiotemporal processing modules.
• 09/23 -2026-
  Weight-Adaptive Physics-Constrained AI Predicts Long-Term Reservoir Pressure from Scarce Data

  A research team from the IndustriaI Control Network and System Department of the Shenyang Institute of Automation(SIA), Chinese Academy of Sciences, has proposed a weight-adaptive residual-enhanced physics-constrained machine learning framework (WR-PCML), which can achieve accurate prediction of the long-term spatiotemporal evolution of reservoir pressure from short-term, small-sample data.
• 09/17 -2026-
  New VLN Agents Move from Instruction Following to Lifelong Intent Understanding

  Recently, a research team from the Shenyang Institute of Automation (SIA) of the Chinese Academy of Sciences, conducted research on intention reasoning and continual autonomous learning in embodied navigation. They proposed ReasonWalker, a navigation agent with implicit instruction reasoning capability, and EverWalker, a lifelong navigation agent with continuous knowledge accumulation and autonomous evolution capability.
• 09/10 -2026-
  SIA Researchers Make Progress in Sparse‑View Satellite‑Image 3D Reconstruction

  A research team from the Shenyang Institute of Automation (SIA) of the Chinese Academy of Sciences, has proposed a new satellite-image 3D reconstruction method named DGR-NeRF. The related work was published in the international journal IEEE Transactions on Geoscience and Remote Sensing under the title Depth and Geometry Regularization for Neural Implicit Reconstruction from Few-View Satellite Images​. Doctoral student LIU Junyuan from the SIA is the first author, and Researchers SHI Zelin and ZHAO Huaici are the corresponding authors.
• 08/28 -2026-
  Laser-Controlled Bubble Microrobots Break Free from 2D Interfaces for 3D Manipulation

  Recently, a research team from the Shenyang Institute of Automation (SIA) of the Chinese Academy of Sciences, proposed a method for multidimensional motion and manipulation of optothermal bubble microrobots based on remote laser control, providing an entirely new technological approach for three-dimensional microscale manipulation, microenvironment construction, and related scenarios.
• 08/28 -2026-
  New Hybrid Ontology Method Resolves Semantic Conflicts Across Manufacturing Systems

  As intelligent manufacturing evolves toward flexibility, networking, and digital twins, systems such as ERP, MES, PLM, and IIoT continuously generate multi-source heterogeneous data. Because these systems are built independently, the same manufacturing object may differ in naming, hierarchy, granularity, and logical constraints across systems, readily causing semantic fragmentation and structural conflicts that constrain cross-system interoperability and manufacturing collaboration. To address this issue, a research team from the IndustriaI Control Network and System Department of the Shenyang Institute of Automation(SIA), Chinese Academy of Sciences, has proposed a consistency-preserving hybrid ontology reconstruction method (HMOR).
• 08/19 -2026-
  Reseachers Develop a Wireless Light-Controlled Biosyncretic Manta Ray Robot with High Mobility

  Inspired by the swimming mechanism of manta rays, a research team from the Shenyang Institute of Automation (SIA) of the Chinese Academy of Sciences (CAS), has developed a wireless near infrared light-controlled biosyncretic manta ray robot powered by isolated bullfrog skeletal muscle. The work was published in the international journal Advanced Functional Materials on August 13.
• 07/29 -2026-
  Researchers Propose Shank-Angle-Driven Control Method for Exoskeleton to Assist Non‑Steady Locomotion

  Recently, a research team from the Robotics Laboratory at the Shenyang Institute of Automation (SIA) of Chinese Academy of Sciences, proposed an intelligent control method for lower-limb exoskeleton robots driven by the shank angle of the human leg. This approach enables the exoskeleton to continuously perceive the human motion state during non‑steady locomotion, achieving continuous matching and bionic coordination between human and robot motion.
• 07/29 -2026-
  Researchers Propose Frequency-Causal Mixture-of-Experts Network for High‑Precision Spinal CT Segmentation

  Automatic segmentation of spinal CT images is a foundational technique for intelligent orthopedic imaging diagnosis, preoperative surgical planning, and intraoperative navigation for spinal robotics. However, the human spine comprises tightly packed vertebral bodies with significant anatomical variations across different segments and complex local textures. To address this challenge, the research team from the Robotics Laboratory at the Shenyang Institute of Automation(SIA) of Chinese Academy of Sciences, proposed a Mixture-of-Experts network via Frequency‑Causal Reasoning (FC‑MoE), offering a novel technical solution for high‑precision automatic segmentation of complex spinal images.
• 07/27 -2026-
  Haidou-1 and Fendouzhe Complete Joint Hadal Scientific Expedition in the Western Pacific

  Supported by the National Key R&D Program project Enhancement of Key Operational Technologies and Scientific Application Capabilities of Haidou-1, the full-ocean-depth Autonomous and Remotely-operated Vehicle (ARV) Haidou-1, developed under the leadership of the Shenyang Institute of Automation (SIA), Chinese Academy of Sciences, has recently completed its sea trial and scientific mission in the high seas of the Philippine Sea, Western Pacific, aboard the research vessel Tansuo-3, and safely returned to port.