Jianhua Zhang

About

Jianhua Zhang is a robotics and computer vision researcher whose work centers on autonomous navigation, simultaneous localization and mapping (SLAM), and intelligent robot perception for real-world industrial and medical environments. His most influential contribution, "Intelligent Collaborative Localization Among Air-Ground Robots for Industrial Environment Perception" (2018, 96 citations), established him as a leading voice in multi-robot systems, demonstrating how coordinated air-ground robot teams can dramatically improve localization accuracy in complex factory settings. Zhang has made sustained contributions to visual SLAM, authoring comprehensive surveys on semantic visual SLAM and developing novel systems that fuse GPS, LiDAR, and building model data for robust real-world mapping. His research extends into human-robot interaction, with notable work on visual focus of attention estimation through eye center localization, and into practical automation, including an industrial sorting system for municipal solid waste. His development of a general UAV simulation platform further reflects a commitment to bridging algorithmic research and real-world deployment. With over 230 cumulative citations spanning sensor fusion, semantic understanding, and autonomous robotics, Zhang's work has meaningfully advanced the state of intelligent, perception-aware robotic systems across industrial, medical, and urban domains.

Research Focus

Key Achievements

Top Papers

1. 1
   Intelligent Collaborative Localization Among Air-Ground Robots for Industrial Environment Perception

   96 citations · 2018
2. 2
   Visual Focus of Attention Estimation Using Eye Center Localization

   27 citations · 2015
3. 3
   Accurate Object Association and Pose Updating for Semantic SLAM

   22 citations · 2022
4. 4
   Semantic Visual Simultaneous Localization and Mapping: A Survey

   19 citations · 2025
5. 5
   Industrial Robot Sorting System for Municipal Solid Waste

   14 citations · 2019
6. 6
   General simulation platform for vision based UAV testing

   13 citations · 2015
7. 7
   GLO-SLAM: a slam system optimally combining GPS and LiDAR odometry

   13 citations · 2021
8. 8
   Accurate real-time visual SLAM combining building models and GPS for mobile robot

   12 citations · 2020
9. 9
   Three dimensional object segmentation based on spatial adaptive projection for solid waste

   9 citations · 2018
10. 10
    Semantic Visual Simultaneous Localization and Mapping: A Survey

    9 citations · 2022

Key Collaborators

Contact & Links