Haojun Xu

Air Force Engineering University

Papers

1

Total Citations

3

H-Index

1

About

Haojun Xu is a researcher at the forefront of robotic perception and intelligent control, with a primary focus on advancing visual localization and manipulation systems. His most notable contribution is the development of a novel framework that fuses 3D Gaussian Splatting—a cutting-edge scene representation technique—with heuristic optimization algorithms to achieve precise, real-time localization of robotic end effectors. This work, published in 2024, addresses critical challenges in unstructured environments by enabling robots to accurately perceive their position and orientation without relying on expensive or fragile sensors. Although still early in its citation trajectory, the paper has already garnered 3 citations, signaling growing interest from the robotics and computer vision communities. Xu’s research bridges the gap between photorealistic 3D reconstruction and practical robotic control, offering a scalable solution for tasks ranging from automated assembly to surgical assistance. His approach stands out for its computational efficiency and robustness, promising to reduce reliance on traditional marker-based tracking systems. As a rising voice in embodied AI, Xu continues to push boundaries at the intersection of graphics, optimization, and robotics, with potential applications in autonomous navigation and human-robot collaboration.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Visual localization of robotic end effector via fusion of 3D Gaussian Splatting and heuristic optimization algorithm
3 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Air Force Engineering University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago