Lintong Wu

Papers

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About

Lintong Wu is a robotics researcher whose work focuses on advancing visual Simultaneous Localization and Mapping (SLAM) for autonomous systems, with a particular emphasis on handling the challenges of dynamic, real-world environments. His most notable contribution, "An Adaptive ORB-SLAM3 System for Outdoor Dynamic Environments" (2023), tackles a critical bottleneck in visual SLAM: the degradation of localization accuracy caused by moving objects that violate static-world assumptions. By introducing an adaptive method to filter out dynamic features from the epipolar geometry, Wu’s approach significantly improves the robustness and precision of SLAM in outdoor settings—a key requirement for applications like autonomous driving and field robotics. With 23 citations since its publication, this work is gaining traction as a practical solution to a long-standing problem. Wu’s research sits at the intersection of computer vision and robotics, aiming to make autonomous navigation more reliable in unpredictable environments. His adaptive SLAM framework represents an important step toward bridging the gap between laboratory-tested algorithms and the messy, dynamic conditions of the real world.