Shuwei Li

Jiangsu University, Southern University of Science and Technology

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About

Shuwei Li is a robotics researcher whose work centers on the intersection of structural dynamics and intelligent perception for autonomous systems. His key research areas include industrial robotics, visual simultaneous localization and mapping (VSLAM), and edge computing for robotic applications. Li made a significant contribution to the modeling of industrial robots by introducing a Blind-Kriging based approach for natural frequency modeling, a method that enhances the accuracy of dynamic simulations for robotic manipulators. This work, published in 2021, has garnered 15 citations, establishing a foundation for improved robot control and design. More recently, Li has advanced the field of VSLAM with his innovative Tensorized-Transformer based Loop Closure Detection (TT-LCD) system. This work addresses a critical challenge in autonomous driving and intelligent robotics—correcting drift and accumulated errors in visual SLAM—by leveraging a novel tensorized transformer architecture optimized for edge devices. The TT-LCD framework represents a notable achievement in making robust loop closure detection computationally efficient for real-world deployment. Through these contributions, Li is helping to bridge the gap between high-fidelity robot modeling and practical, on-device intelligence for next-generation autonomous systems.