Papers
2
Total Citations
11
H-Index
2
About
Shuxin Qiu is a rising researcher in robotics and autonomous systems, whose work tackles the critical challenge of sensor fusion for reliable perception in complex environments. His primary research areas include multi-sensor calibration, simultaneous localization and mapping (SLAM), and state estimation for mobile robots and autonomous vehicles. Qiu’s major contributions lie in developing robust, real-time algorithms that maximize the utility of limited sensor data. His paper "LiDAR-Link" (2024, 7 citations) addresses a pressing industry problem: the extrinsic calibration of multiple solid-state LiDARs with non-overlapping fields of view, introducing an observability-aware probabilistic plane-based method that enables accurate sensor alignment without requiring shared visual data. This work is vital for scaling perception systems in autonomous driving. Complementing this, his paper "R²DIO" (2023, 4 citations) presents a robust depth-inertial odometry system that leverages multimodal constraints from RGB-D cameras to maintain accurate localization in challenging indoor environments where traditional SLAM systems fail. By computationally fusing depth and inertial data, Qiu’s approach achieves real-time performance without sacrificing robustness. His work demonstrates a keen ability to solve practical, hardware-driven problems, making him a notable contributor to the next generation of autonomous navigation systems.
Research Focus
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Top Papers
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