Muhua Zhang
Papers
7
Total Citations
41
H-Index
4
About
Muhua Zhang is a leading researcher in autonomous robotics, specializing in laser-based simultaneous localization and mapping (SLAM), motion planning, and intelligent inspection systems for constrained industrial environments. Zhang’s major contributions include developing hybrid-dimensional SLAM frameworks that enable quadruped robots to balance movement flexibility with precise navigation, and high-precision sampling-based motion planners like Path-Follower that allow large inspection robots to follow pre-planned paths in narrow spaces without autonomous obstacle avoidance. Their work on under-vehicle inspection robots integrates 3D solid-state LiDAR with dedicated SLAM and relocalization methods to correct odometry errors and ensure safe operation in hazardous settings. With over 40 citations across key papers, Zhang’s impact is evident in advancing autonomous navigation for real-world industrial applications. Notably, Zhang introduced InspectionGPT, a large language model-based system that enhances cognitive decision-making for inspection task planning, bridging robotics and AI. Their 2025 work on high-traversability navigation further demonstrates integrated sensing-planning systems for tight spaces, solidifying Zhang’s reputation as an innovator in practical, deployable robotic solutions for challenging environments.
Research Focus
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Top Papers
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