LI Lei-min

Changchun University of Science and Technology, Southwest University of Science and Technology

Papers

Total Citations

H-Index

About

Li Lei-min’s research lies at the intersection of robotics, artificial intelligence, and computer vision, with a focus on enabling intelligent systems to perceive and cooperate in dynamic environments. A key contribution is his work on multi-robot cooperation, where he addressed the complex challenge of task allocation by proposing a pyramid-like hybrid control architecture that blends centralized and distributed control strategies. This framework, grounded in multi-agent systems (MAS) and sensor information, provides a scalable solution for coordinating multiple robots in real-world tasks. In the domain of computer vision, Lei-min developed an algorithm for feature detection and matching in traffic sign images, integrating shape detection, Harris corner detection, and SIFT feature matching with robust estimation methods. This work is critical for mobile robot localization and navigation, enhancing a robot’s ability to interpret its surroundings. While his most-cited papers have garnered modest citation counts—3 and 2 respectively—they represent foundational steps in practical robotics. Lei-min’s contributions are particularly notable for bridging theoretical control architectures with applied sensor-driven perception, offering valuable insights for researchers in autonomous systems and cooperative robotics.