Ke Wu

Papers

Total Citations

H-Index

About

Ke Wu is a leading researcher in robotics and autonomous systems, with a primary focus on active scene reconstruction, 3D perception, and intelligent planning for unknown environments. His most notable contribution is the development of **HGS-Planner**, a hierarchical planning framework that leverages 3D Gaussian Splatting for real-time, high-quality scene reconstruction. This work addresses a critical challenge in robotics: enabling autonomous agents to intelligently explore and map complex, unstructured environments—such as those encountered in search and rescue missions—while maintaining both reconstruction fidelity and computational efficiency. By integrating active perception with advanced 3D representation learning, Wu’s research bridges the gap between real-time situational awareness and robotic decision-making. His HGS-Planner paper, published in 2025, has already garnered 5 citations, signaling its rapid impact on the field. Wu’s work is distinguished by its practical orientation: rather than treating reconstruction as a passive post-processing step, he frames it as an active, goal-driven process that directly informs robot behavior. This approach has significant implications for disaster response, autonomous exploration, and industrial inspection. As a rising scholar, Ke Wu is shaping the next generation of intelligent robotics that can see, understand, and act in real time.