Papers
20
Total Citations
433
H-Index
11
About
Jianhao Jiao is a robotics researcher whose work sits at the intersection of simultaneous localization and mapping (SLAM), multi-sensor fusion, and autonomous navigation. His research addresses some of the most persistent challenges in mobile robotics: enabling robots to reliably perceive, map, and localize themselves across diverse and demanding real-world environments. Jiao's most influential contribution, "Robust Odometry and Mapping for Multi-LiDAR Systems With Online Extrinsic Calibration" (2021, 124 citations), introduced a unified framework for fusing multiple LiDAR sensors while simultaneously calibrating their spatial relationships — a significant advance for robust autonomous systems. His development of the FusionPortable benchmark datasets (2022, 2024) has provided the research community with richly annotated, multi-sensor data across varied platforms, directly supporting reproducible SLAM evaluation. Beyond data and system design, Jiao has made theoretical contributions through globally optimal solutions to pose estimation and LiDAR-camera calibration problems, and has extended perception capabilities to semantic mapping and place recognition. His 2025 survey on place recognition further reflects his growing role as a synthesizer of the field's progress. With over 360 cumulative citations across his top works, Jiao's research consistently bridges rigorous mathematical foundations with practical deployment, making him a notable voice in modern autonomous robotics research.
Research Focus
Key Achievements
Top Papers
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- 4R-PCC: A Baseline for Range Image-based Point Cloud Compression31 citations · 2022
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- 6General Place Recognition Survey: Toward Real-World Autonomy24 citations · 2025
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- 10Towards a Cloud Robotics Platform for Distributed Visual SLAM14 citations · 2017