Chen-Hsuan Ma
Papers
1
Total Citations
3
H-Index
1
About
Chen-Hsuan Ma is a researcher specializing in autonomous navigation, sensor fusion, and robotic localization. His most-cited work, "Outdoor Positioning Based on ROS LiDAR Navigation Compared with RTK GPS Accuracy" (2023, 3 citations), makes a significant contribution to field robotics by systematically evaluating the precision of ROS-based 2D LiDAR SLAM against high-accuracy RTK GPS. Ma's study implements two particle-filtering algorithms—gmapping (Grid-based FastSLAM) for map construction and adaptive Monte Carlo localization (AMCL) for pose estimation—demonstrating that cost-effective LiDAR systems can achieve competitive outdoor positioning accuracy. This work bridges the gap between indoor SLAM research and real-world outdoor deployment, offering practical validation for autonomous ground vehicles operating in GPS-denied or degraded environments. By benchmarking ROS navigation stacks against centimeter-level GPS references, Ma provides crucial performance baselines for researchers and engineers developing low-cost autonomous systems. His findings directly inform the design of robust localization pipelines for agricultural robots, delivery drones, and mobile service robots, highlighting the viability of LiDAR-based navigation as a reliable alternative to expensive GPS equipment.
Research Focus
Key Achievements
Top Papers
- 1