Mengying Sun

Southern University of Science and Technology

Papers

1

Total Citations

2

H-Index

1

About

Mengying Sun is a researcher advancing the frontiers of autonomous mobile robotics through innovations in hardware-accelerated visual-inertial odometry (VIO). Her work focuses on reconfigurable computing architectures that dramatically improve the area and energy efficiency of real-time localization systems—a critical challenge for resource-constrained robots. In her most cited paper (2022), she introduced a novel VIO accelerator core that achieves high performance while maintaining low power consumption, enabling AMRs to navigate complex environments with minimal computational overhead. This contribution addresses the fundamental tension between algorithmic complexity and hardware efficiency in robotic perception. While her citation count is still growing, her work represents an important step toward practical, deployable autonomous systems. By bridging the gap between sophisticated VIO algorithms and energy-efficient hardware implementation, Sun is helping to make autonomous mobile robots more accessible for applications ranging from industrial automation to service robotics. Her research sits at the intersection of computer architecture, embedded systems, and robotics—a promising direction for the next generation of intelligent machines.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
A Reconfigurable Visual–Inertial Odometry Accelerated Core with High Area and Energy Efficiency for Autonomous Mobile Robots
2 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: Southern University of Science and Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago