Guohao Tang

Guilin University of Electronic Technology

Papers

Total Citations

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About

Guohao Tang is a researcher specializing in multi-sensor fusion, robotics localization, and intelligent navigation systems. His major contribution lies in advancing odometry techniques for indoor mobile robots, particularly through the integration of wheel, inertial, and visual sensors. In his highly cited 2024 work, "Multi-Sensor Fusion for Wheel-Inertial-Visual Systems Using a Fuzzification-Assisted Iterated Error State Kalman Filter," Tang addresses the critical problem of odometry drift in differential-drive robots. He introduces a novel Fuzzy Inference System (FIS) within a Wheel-Inertial-Visual Odometry (WIVO) framework, optimizing 6-DoF localization in unstructured environments. This work has already garnered 7 citations, underscoring its immediate relevance and impact in the field. Tang’s research is notable for its practical application to real-world robotics challenges, offering robust solutions for autonomous navigation. His achievements demonstrate a strong command of sensor fusion and adaptive filtering, positioning him as an emerging expert in intelligent robotic systems.