Jiaqi Zhong

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About

Jiaqi Zhong is a researcher in robotics and computer vision, with a primary focus on simultaneous localization and mapping (SLAM) systems for dynamic environments. Their most cited work, "Dynamic point-line SLAM based on lightweight object detection" (2025), introduces a novel approach that integrates point and line features with efficient object detection to robustly handle moving objects in real-world scenes—a critical challenge for autonomous navigation. This paper, already garnering 6 citations shortly after publication, demonstrates Zhong's ability to address practical limitations in traditional SLAM by balancing accuracy and computational efficiency. Their contributions lie in advancing SLAM's adaptability to dynamic surroundings, which has direct implications for autonomous vehicles, drones, and augmented reality. By leveraging lightweight neural networks for object detection, Zhong's work reduces the computational overhead typically associated with dynamic SLAM, making it more deployable on resource-constrained platforms. This research marks a significant step toward reliable, real-time mapping in cluttered or changing environments, positioning Zhong as an emerging voice in the intersection of robotics and deep learning.