Research
I'm broadly interested in the overlap between robotics and computer vision, specifically, my research focuses the on use of Deep learning to solve the real problems of Robotics applications.
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News
[Mar 2024] We submitted the UMAD dataset to IROS 2024!
[Mar 2024] A new personal website has been created.
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UMAD: University of Macau Anomaly Detection Benchmark Dataset
Dong Li, Lineng Chen, Cheng-Zhong Xu, Hui Kong
Submit to IROS, 2024
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A large-scale reference-based anomaly detection benchmark dataset that captures real-world scenarios. UMAD is applicable for both Change Detection and Anomaly Detection tasks.
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GitHub Repository: awesome-Implicit-NeRF-SLAM
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A comprehensive list of Implicit Representations, NeRF and 3D Gaussian Splatting papers relating to SLAM/Robotics domain, including papers, videos, codes, and related websites.
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Undergraduate Project, 2018-2022
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During my undergraduate studies, I worked on several projects related to robotics and electronics, including Unmanned Surface Vehicle (USV), Underwater Robot, Intelligent Sorting Trash Can, Automatic Tracking, Identification, and Measuring Device, SLAM-based Mobile Robot, and Robomaster Robots. For more information, please refer to the document.
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The Applications of Fiducial Markers in Robotic Grasping: A Comparison Between AprilTag and ArUco Markers, 2023
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This paper investigates the possible applications of two fiducial markers (AprilTag and ArUco) on hand eye calibration and localization procedures in a robotic grasping task and compares their performance on each procedure under different lighting conditions.
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Robotics Projects at SUSTech, 2022-2023
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While I was a Research Assistant at SUSTech, I developed various robotic platforms, including mobile robots and robotic arms. I utilized a range of sensors such as 2D/3D Lidar, depth cameras, millimeter-wave radar, and RFID, I implemented V-SLAM(ORB-SLAM, VINS, and RTAPMAP), Lidar-SLAM(Cartographer, LOAM/Lego-LOAM). I also developed a grasping system based on tags.
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