Qinxuan Sun
Papers
10
Total Citations
180
H-Index
6
About
Qinxuan Sun is a leading researcher in mobile robotics, specializing in simultaneous localization and mapping (SLAM), human-robot interaction, and place recognition for autonomous navigation. Sun’s most impactful contribution is the development of **Plane-Edge-SLAM** (72 citations), which pioneered the seamless fusion of planar and edge features to overcome degradation in indoor SLAM, significantly improving robustness under challenging lighting conditions. In human-robot collaboration, Sun introduced a **laser-based intersection-aware human following** system (37 citations) that addresses the critical problem of target occlusion at corridor turns, and later enhanced this with a fusion of skeleton recognition and face tracking (14 citations). Sun also advanced visual place recognition with a **two-level spatial relation graph framework** (17 citations) and an **interpretation tree-based visual odometry** method (14 citations) that leverages hybrid geometric features for higher accuracy. More recently, Sun proposed **adaptive soft encoding** (2023), an unsupervised feature aggregation technique for place recognition. With over 180 total citations across ten publications, Sun’s work directly addresses real-world deployment challenges for service robots, making autonomous navigation more reliable in complex indoor environments.
Research Focus
Key Achievements
Top Papers
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- 5A Novel Approach to Image-Sequence-Based Mobile Robot Place Recognition14 citations · 2019
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- 7A Novel SLAM Method Using Wi-Fi Signal Strength and RGB-D Images5 citations · 2018
- 8An Improved ORB-SLAM2 With Refined Depth Estimation3 citations · 2019
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