Papers
1
Total Citations
15
H-Index
1
About
Yiren Hao is a researcher focused on advancing autonomous navigation systems, with a particular emphasis on 3D LiDAR-based environmental perception and mapping. Their most cited work, "An Effective Way of Constructing Static Map Using 3-D LiDAR for Autonomous Navigation in Outdoor Environments" (2023), addresses a critical challenge in mobile robotics: the interference of dynamic objects in LiDAR measurements. Hao’s contribution lies in developing a method to filter out moving entities—such as pedestrians or vehicles—to generate accurate, static maps essential for reliable localization and path planning. This work, with 15 citations, demonstrates Hao’s impact in enhancing the robustness of autonomous systems in real-world, uncontrolled settings. By tackling the inconsistency between dynamic environments and static map requirements, Hao has provided a practical solution that bridges a gap in outdoor navigation research. Their efforts are particularly valuable for students and engineers working on self-driving cars, delivery robots, or field robotics, where precise mapping is paramount. Hao’s research underscores a commitment to making autonomous navigation safer and more effective, marking them as a promising voice in the field of robotics and perception systems.
Research Focus
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Top Papers
- 1