Shenliang Li

Papers

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About

Shenliang Li is a robotics researcher specializing in lidar-based localization, mapping, and navigation for mobile robots. His work addresses critical challenges in deploying low-cost sensors with limited field of view (FoV) in real-world autonomous systems. Li’s major contributions include developing robust lidar-inertial odometry (LOAM) frameworks that integrate real-time relocalization capabilities, enabling robots to accurately determine their position within pre-built maps even with constrained sensor hardware. His 2021 paper on a low-cost mapping and relocalization system, which has garnered early citations, demonstrates a practical approach to overcoming the feature scarcity issues inherent in small-FoV lidars. A related study on 6-DOF localization in 3D feature point maps further refines these techniques, offering a reliable solution for LiDAR-based navigation without expensive, wide-angle sensors. While his citation counts are still growing, Li’s work is foundational for cost-effective autonomous navigation, with direct applications in service robots, warehouse automation, and field robotics. His research bridges the gap between theoretical SLAM algorithms and deployable, budget-constrained systems—a vital step toward democratizing advanced robotic capabilities.