Papers
2
Total Citations
25
H-Index
2
About
Zewu Gong is a robotics researcher whose work bridges the gap between autonomous navigation and bio-inspired locomotion. His primary research areas include multi-robot cooperative SLAM (simultaneous localization and mapping) and vision-based pose estimation for legged systems. Gong’s most cited work, “A SLAM Method Based on Multi-Robot Cooperation for Pipeline Environments Underground” (2022, 17 citations), addresses the critical challenge of deploying autonomous robots in GPS-denied, geometrically sparse underground infrastructure—a domain where traditional laser-vision fusion strategies often fail. This contribution is vital for industrial inspection and disaster response robotics. Complementing this, his paper “Vision-Based Quadruped Pose Estimation and Gait Parameter Extraction Method” (2022, 8 citations) tackles the complex problem of extracting precise kinematic data from diverse quadruped species. This work has dual significance: advancing ethological studies of animal health and behavior, while providing essential gait parameters for designing more agile legged robots. By developing methods that work across species with radically different morphologies, Gong is helping to create more versatile and adaptive robotic systems. His research demonstrates a clear trajectory from robust environmental mapping to understanding and replicating animal locomotion, positioning him as a promising contributor to field robotics and bio-inspired engineering.
Research Focus
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Top Papers
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