Su Qin

Chongqing University of Posts and Telecommunications

Papers

Total Citations

H-Index

About

Su Qin is a researcher specializing in robotics, sensor fusion, and simultaneous localization and mapping (SLAM), with a particular focus on improving the robustness and accuracy of autonomous navigation in mobile robots. Their most notable contribution is the development of an improved Rao-Blackwellized H∞ filter for SLAM, which addresses the limitations of traditional filtering methods in the presence of non-Gaussian noise and model uncertainties. This work, published in 2016, has garnered 5 citations and represents a meaningful step toward more reliable state estimation in challenging environments. By integrating H∞ filtering techniques with Rao-Blackwellized particle filters, Qin’s approach enhances the resilience of SLAM systems, making them better suited for real-world applications where sensor data may be corrupted or incomplete. While their citation count is modest, the technical depth and practical relevance of their research underscore a focused commitment to advancing the foundational algorithms that underpin autonomous robot navigation. Su Qin’s work serves as a valuable reference for researchers and students seeking to explore robust filtering strategies in mobile robotics.