Yuwei Cai

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About

Yuwei Cai is a researcher at the forefront of autonomous systems and intelligent infrastructure, whose work bridges the gap between bio-inspired robotics and practical deep learning applications. In their highly cited 2023 paper, "VG-Swarm," Cai introduced a novel vision-based gene regulatory network (V-GRN) that enables UAV swarms to achieve dynamic encirclement through decentralized, biologically inspired behavior emergence. This work, which has garnered 17 citations, represents a significant leap in swarm robotics by combining visual perception with gene regulation principles, allowing each aerial robot to autonomously coordinate its spatial positioning without centralized control. Prior to this, Cai made notable contributions to infrastructure inspection with "Automatic Pavement Crack Detection Based on YOLOv5-AH" (2022, 7 citations), where they addressed the challenge of detecting pavement cracks under complex backgrounds and varying scales. By enhancing the YOLOv5 architecture, Cai developed a robust deep learning model that improves the accuracy and reliability of automated road condition assessment. Their research demonstrates a unique ability to transfer biological principles into engineering solutions, from swarm coordination to infrastructure monitoring, establishing Cai as an innovator in both autonomous robotics and applied computer vision.