Ming-Chun Lin

China University of Science and Technology

Papers

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About

Ming-Chun Lin is a leading researcher in autonomous robotics, specializing in visual perception, simultaneous localization and mapping (SLAM), and dynamic object tracking. His most influential work, "Visual SLAM and Moving-object Detection for a Small-size Humanoid Robot" (2010, 44 citations), introduced a novel moving object detection (MOD) algorithm that integrates with visual SLAM, treating moving objects as rigid bodies with spatial coordinates defined by position vectors and rotation matrices. This contribution significantly advanced the ability of humanoid robots to navigate dynamic environments. Lin also made key strides in mobile robotics with "Dynamic Object Tracking Control for a Non-Holonomic Wheeled Autonomous Robot" (2009, 14 citations), where he developed motion control laws using Lyapunov’s direct method and computed-torque methods, enabling real-time image processing for robust tracking. His work bridges theoretical control systems and practical robot vision, offering foundational solutions for autonomous navigation in cluttered, changing spaces. With a focus on real-time performance and rigorous mathematical modeling, Lin’s research continues to inspire innovations in service robotics and autonomous vehicles.