Haowu Zhao

Papers

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About

Haowu Zhao is a robotics researcher specializing in multi-sensor fusion for autonomous navigation, with a particular focus on LiDAR-inertial odometry and visual marker-aided localization. His most cited work, "Marked-LIEO: Visual Marker-Aided LiDAR/IMU/Encoder Integrated Odometry" (2022), addresses a critical challenge in indoor mobile robotics: maintaining accurate pose estimation in feature-sparse environments like long corridors. Zhao’s key contribution lies in developing a tightly-coupled fusion framework that integrates visual markers with LiDAR, IMU, and encoder data, enabling robust localization where traditional methods fail. By designing pre-integration models for both encoder and IMU measurements, his approach achieves reliable state estimation even under degraded visual conditions. With 10 citations, this work has already influenced research in resilient robot navigation. Zhao’s research bridges the gap between visual landmark systems and inertial-based odometry, offering practical solutions for real-world deployment in warehouses, tunnels, and other GPS-denied settings. His ongoing work continues to advance the reliability of autonomous mobile robots in challenging indoor environments.