Zhongli Ma

Chengdu University of Information Technology

Papers

Total Citations

H-Index

About

Zhongli Ma is a robotics researcher specializing in computer vision, simultaneous localization and mapping (SLAM), and intelligent robotic manipulation. His work focuses on improving the perception and autonomy of mobile and industrial robotic systems through advanced sensor fusion and deep learning techniques. Ma’s major contributions include developing a vision-based robotic arm sorting method using an improved YOLOv5 algorithm, which significantly reduces error rates and enhances real-time performance in industrial settings. He has also advanced SLAM technology by proposing an enhanced LIO-SAM lidar-inertial odometer that incorporates dynamic point filtering and Iris loop detection for more robust trajectory estimation and mapping. Additionally, his research on point cloud roughness-based feature extraction provides more reliable methods for constructing environmental maps. With over 9 citations across his key publications, Ma’s work is gaining recognition for addressing critical challenges in real-time perception and localization. His notable achievements include designing a complete vision robotic arm testing platform and integrating novel loop detection into state-of-the-art SLAM frameworks, demonstrating a strong commitment to bridging theoretical research with practical, deployable solutions for intelligent robotics.