Shanliang Chen

Huazhong University of Science and Technology

Papers

Total Citations

H-Index

About

Shanliang Chen is a robotics and autonomous systems researcher whose work centers on simultaneous localization and mapping (SLAM), pose estimation, and sensor fusion for mobile robots. His research tackles one of the most persistent challenges in autonomous navigation: achieving accurate, robust self-localization in complex, real-world environments where individual sensors fall short. Chen's most notable contributions involve developing tightly coupled multi-sensor SLAM frameworks that intelligently integrate monocular cameras, inertial measurement units (IMUs), and wheel odometry. His 2020 paper on wheel speed anomaly detection — his most cited work with 14 citations — addresses a particularly practical problem: maintaining reliable pose estimation even when a robot experiences slipping, collision, or wheel abduction, events that commonly corrupt navigation in unstructured settings. By embedding anomaly detection directly into the SLAM pipeline, Chen's approach significantly improves system resilience under real-world disturbances. His complementary work on robust tightly coupled pose estimation further demonstrates his commitment to bridging the gap between monocular vision's scale ambiguity and the demands of practical ground robot deployment. Though still building his citation profile, Chen's focused contributions to fault-tolerant, multi-modal SLAM offer meaningful advances for researchers and engineers working on reliable autonomous mobile robotics.