Papers
2
Total Citations
11
H-Index
2
About
Yichong Jia is a robotics researcher advancing the frontier of autonomous navigation in complex, dynamic environments. His primary research areas center on LiDAR-based simultaneous localization and mapping (SLAM), dynamic object tracking, and robust perception for ground robots operating in unstructured terrain. Jia’s most notable contribution is the development of **TRLO** (2025), an efficient LiDAR odometry framework that simultaneously performs state estimation and mapping while tracking and removing 3D dynamic objects. This work directly addresses a critical limitation of traditional SLAM systems—their reliance on a static world assumption—enabling reliable robot operation amidst moving vehicles and pedestrians in urban settings. With 9 citations, TRLO has quickly gained recognition for its practical impact. Additionally, Jia introduced **M2UD** (2025), a multi-model, multi-scenario, uneven-terrain dataset specifically designed for evaluating ground robot localization and mapping. This resource fills a crucial gap in the field by providing challenging, real-world data for benchmarking, earning early citations. Through these contributions, Yichong Jia is helping to make autonomous robots safer and more capable in the messy, dynamic world they must navigate.
Research Focus
Key Achievements
Top Papers
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