Mujiao Ouyang

Southeast University

Papers

1

Total Citations

10

H-Index

1

About

Mujiao Ouyang is a leading researcher in robotics navigation, specializing in multi-sensor fusion for autonomous systems operating in GNSS-denied environments. Their most impactful work, "Tightly Coupled LIDAR/IMU/UWB Fusion via Resilient Factor Graph for Quadruped Robot Positioning" (2024, 10 citations), addresses a critical challenge: maintaining continuous, accurate positioning for robots in environments where satellite signals are unavailable. Ouyang's major contribution lies in developing a resilient factor graph framework that tightly integrates LiDAR, inertial measurement units (IMUs), and ultra-wideband (UWB) sensors. This approach significantly enhances the robustness and accuracy of quadruped robot positioning, particularly in challenging terrains where traditional methods fail. By overcoming the limitations of LiDAR-IMU systems in degraded visual conditions, Ouyang's work advances the practical deployment of legged robots for search-and-rescue, industrial inspection, and exploration missions. Their research bridges the gap between theoretical sensor fusion and real-world robotic navigation, offering a scalable solution for autonomous systems. With a growing citation record, Ouyang is recognized for pushing the boundaries of resilient positioning technology, making them a rising figure in the field of field robotics.

Research Focus

Key Achievements

1
H-Index
1
Papers
10
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Tightly Coupled LIDAR/IMU/UWB Fusion via Resilient Factor Graph for Quadruped Robot Positioning
10 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Southeast University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago