Papers
12
Total Citations
182
H-Index
7
About
Guolai Jiang is a leading researcher in mobile robotics, specializing in simultaneous localization and mapping (SLAM), sensor fusion, and autonomous navigation for service and surveillance robots. His most impactful work, cited 72 times, introduces a SLAM framework that fuses low-cost LiDAR with vision to build 2.5D maps, addressing the critical challenge of error accumulation in price-sensitive consumer robots. Jiang further advanced low-cost SLAM with an FFT-based scan-matching method (27 citations), significantly improving accuracy for robots using noisy laser range finders. His research extends to practical indoor navigation, including door detection and crossing using Kinect depth images (17 citations), enabling large surveillance robots to autonomously patrol complex environments. Jiang has also contributed to dynamic environment perception with a semantic geometric fusion multi-object tracking system (2024) and developed a lightweight multimodal person re-identification metric for person-following robots (2023). With over 180 total citations across his publications, Jiang’s work bridges the gap between theoretical SLAM algorithms and real-world deployment, making autonomous robots more accessible, reliable, and capable in everyday settings like restaurants, homes, and surveillance routes.
Research Focus
Key Achievements
Top Papers
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- 3Detecting, locating and crossing a door for a wide indoor surveillance robot17 citations · 2013
- 4An approach to restaurant service robot SLAM14 citations · 2016
- 5Kinect depth image based door detection for autonomous indoor navigation12 citations · 2014
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- 8On study of a wheel-track transformation robot7 citations · 2015
- 9On real-time obstacle avoidance using 3-D point clouds6 citations · 2014
- 10Road detection at night based on a planar reflection model4 citations · 2013