Papers
8
Total Citations
176
H-Index
5
About
Wu H is a leading researcher in mobile robotics, specializing in autonomous navigation, path planning, and 3D perception. Their work addresses critical challenges in robot mobility, from overcoming physical obstacles to navigating dynamic environments. A central contribution is the development of a fusion algorithm combining a kinematically constrained A* algorithm with the Dynamic Window Approach for mobile robot path planning, a highly cited work (55 citations) that improves upon traditional methods. Wu H has also advanced localization techniques, proposing an improved LiDAR localization method using multi-sensing data (51 citations), enabling robust navigation without GNSS. Their innovative approach extends to trajectory optimization for adaptive deformed wheels using a hybrid genetic and particle swarm optimization algorithm, as well as deep reinforcement learning for dynamic obstacle avoidance. Beyond navigation, Wu H has made notable contributions to 3D reconstruction, including a real-time dense reconstruction model using deep multiview stereo and sensor fusion. With over 175 total citations across their most-cited papers, Wu H’s research is shaping the future of intelligent, autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Improved LiDAR Localization Method for Mobile Robots Based on Multi-Sensing51 citations · 2022
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- 7An Environment Recognition Algorithm for Staircase Climbing Robots2 citations · 2024
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