Lu Guokun

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About

Lu Guokun is a leading researcher in mobile robotics and autonomous navigation, with a primary focus on simultaneous localization and mapping (SLAM) and rescue robotics. His most influential work, "SLAM Algorithm Analysis of Mobile Robot Based on Lidar" (2019), has garnered 80 citations, establishing a foundational framework for testing SLAM algorithms in indoor environments using the Robot Operating System (ROS) and Gazebo simulator. This research directly addresses the challenges of urban search and rescue (USAR) scenarios, demonstrating how lidar-based SLAM can enable robots to navigate hazardous, unstructured disaster zones autonomously. Lu’s complementary survey on RoboCup rescue robot technologies (2019, 10 citations) systematically reviews key advancements in deploying robots for earthquake response, firefighting, and other life-threatening emergencies. His contributions bridge the gap between theoretical SLAM algorithms and practical deployment in high-risk environments, offering critical insights for improving robot autonomy in disaster response. By integrating ROS-based simulation with real-world rescue constraints, Lu’s work has become a cornerstone for researchers developing resilient navigation systems for mobile robots operating in unpredictable, dangerous conditions.