Bushi Chen

About

Bushi Chen is a leading researcher in autonomous robotics, specializing in state estimation, sensor fusion, and lifelong SLAM for mobile robots. Their major contributions center on developing robust, real-time navigation systems that integrate LiDAR, inertial measurement units (IMUs), GNSS, and wheel odometry. Chen’s most cited work, "LIO-Fusion" (2023, 31 citations), introduces a reinforced LiDAR-inertial odometry framework that fuses GNSS and wheel odometry to deliver accurate 6-DoF movement estimation in complex environments—a critical advancement for autonomous navigation. Building on this, "SLAM-RAMU" (2024, 7 citations) extends the paradigm to lifelong SLAM, enabling autonomous map updating and relocalization in dynamic settings, directly addressing challenges faced by autonomous mobile robots (AMRs) in industrial and service applications. These innovations have established Chen as a key figure in reliable, multi-sensor navigation, with work cited for its practical impact on real-world robotics. Their research bridges theoretical sensor fusion with deployable solutions, making them a notable contributor to the field of autonomous systems.

Research Focus

Key Achievements

Top Papers

1. 1
   LIO-Fusion: Reinforced LiDAR Inertial Odometry by Effective Fusion With GNSS/Relocalization and Wheel Odometry

   31 citations · 2023
2. 2
   SLAM-RAMU: 3D LiDAR-IMU lifelong SLAM with relocalization and autonomous map updating for accurate and reliable navigation

   7 citations · 2024

Key Collaborators

Contact & Links