Max Robotics — Global Service Robot Directory + US Certification

About

Ha Sier is a rising star in autonomous robotics, specializing in multi-modal perception and state estimation for GNSS-denied environments. His research centers on LiDAR-based SLAM, sensor fusion, and odometry, with a particular focus on leveraging novel LiDAR-as-a-camera sensors that bridge the gap between 3D point clouds and visual imagery. Sier’s most impactful work includes a benchmark for multi-modal LiDAR SLAM (29 citations) and a pioneering study on UAV tracking using LiDAR as a camera sensor (30 citations), both providing critical ground-truth datasets and algorithms for systems operating without GPS. He has also advanced point cloud registration by exploiting keypoints derived from LiDAR-generated images, improving odometry estimation accuracy. More recently, his survey on event-based sensor fusion for odometry (2025) synthesizes the state of the art in combining asynchronous event cameras with traditional sensors for high-speed, low-light scenarios. With over 70 cumulative citations in just two years, Sier’s contributions are shaping the next generation of robust, perception-driven autonomy for drones and ground robots in challenging, GPS-denied settings.