Yaning Zhai

Guilin University of Electronic Technology

Papers

Total Citations

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About

Yaning Zhai is a researcher specializing in multi-sensor fusion, robotics localization, and autonomous navigation, with a particular focus on improving odometry accuracy for indoor mobile robots. Their most notable contribution is the development of a novel Wheel-Inertial-Visual Odometry (WIVO) framework that integrates a Fuzzy Inference System (FIS) within an Iterated Error State Kalman Filter. This approach effectively addresses the persistent challenge of odometry drift in differential-drive robots operating in unstructured environments, achieving precise 6-DoF localization by fusing wheel encoders, inertial sensors, and visual data. The work, published in 2024, has already garnered 7 citations, signaling its immediate relevance to the robotics community. Zhai’s research bridges the gap between classical estimation theory and adaptive fuzzy logic, offering a robust solution for real-world applications such as warehouse automation and service robotics. Their innovative use of fuzzification to dynamically tune sensor fusion parameters marks a significant step forward in resilient robot navigation, making their work essential reading for researchers tackling sensor degradation and environmental uncertainty in autonomous systems.