Papers
2
Total Citations
18
H-Index
2
About
Popo Gui is a robotics researcher specializing in simultaneous localization and mapping (SLAM) and industrial manipulation, with a focus on low-cost sensor systems and cluttered environments. Their most cited work introduces a novel loop closure detection approach using simplified structure for low-cost LiDAR, directly addressing the critical challenge of cumulative error in SLAM to improve global localization stability for robot navigation. This foundational contribution has garnered 13 citations, establishing Gui’s expertise in efficient, real-world SLAM solutions. In a complementary study on accurate rapid grasping of small industrial parts from charging trays in clutter scenes, Gui developed a practical RGB-D-based method for detecting and estimating the fine pose of textureless, dark objects on production lines. This work, with 5 citations, demonstrates their ability to solve demanding industrial automation problems where traditional vision systems fail. Together, these contributions highlight Gui’s impact on both autonomous navigation and manufacturing robotics, offering scalable, sensor-efficient approaches that advance the state of the art in low-cost robotic perception and manipulation.
Research Focus
Key Achievements
Top Papers
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