Yiren Huang

Guilin University of Electronic Technology, Guilin University of Aerospace Technology

Papers

Total Citations

H-Index

About

Yiren Huang’s research focuses on advancing autonomous robotics through sensor fusion, simultaneous localization and mapping (SLAM), and machine vision for industrial automation. Huang’s major contributions include developing a novel SLAM mapping method that fuses lidar and depth camera data, overcoming the limitations of single-sensor systems in complex environments—a foundational approach for robust mobile robot navigation. Additionally, Huang created a systematic evaluation framework for SLAM algorithms using the ROS_Gazebo simulation platform, enabling precise trajectory and environmental parameter analysis without costly real-world trials. In industrial applications, Huang integrated robot vision with coordinate systems for automated production lines, specifically for laser quenching processes, demonstrating practical improvements in workpiece positioning and grasping. While early in their career, Huang’s work has already garnered citations (3 for the SLAM fusion paper, 2 each for the evaluation and industrial applications papers), signaling growing recognition. These contributions are particularly notable for bridging theoretical SLAM advances with tangible industrial robotics solutions, offering valuable insights for researchers and engineers seeking to enhance autonomous system reliability and efficiency in real-world settings.