Huanwei Wang

Papers

Total Citations

144

H-Index

About

Huanwei Wang is a researcher specializing in intelligent path planning and mobile robot navigation, with a focus on enhancing classical algorithms for real-world autonomy. His major contributions lie in improving the efficiency and safety of autonomous navigation systems. Wang’s most influential work, “The EBS-A* algorithm: An improved A* algorithm for path planning” (2022), has garnered 130 citations, demonstrating its significant impact on the field. This algorithm addresses critical limitations of the traditional A* method, such as slow planning speed and unsafe proximity to obstacles, by introducing an enhanced heuristic search that accelerates pathfinding while maintaining safer trajectories. Building on this foundation, Wang’s more recent work, “ETQ-learning: an improved Q-learning algorithm for path planning” (2024), extends reinforcement learning techniques to path planning, further showcasing his commitment to advancing adaptive navigation strategies. Through these contributions, Wang has established himself as a key figure in developing practical, high-performance algorithms for autonomous systems, bridging the gap between theoretical optimization and real-world robotic applications.