Papers

4

Total Citations

38

H-Index

3

About

Liu Liu is a leading researcher in energy-efficient robotic vision and autonomous navigation, with a focus on enabling real-time performance on resource-constrained mobile systems. Her major contributions center on runtime frameworks for heterogeneous architectures, most notably the Π-RT system, which dynamically manages task execution across multiple accelerators and the cloud to achieve significant energy savings while maintaining real-time performance—a critical advancement for autonomous robots. This work, her most cited with 19 citations, demonstrates how to balance performance and power in mobile robotics. Liu also developed SPINS, a navigation system that fuses inertial sensing with prior-map localization using point, line, and plane features, enhancing stability in structure-rich environments (11 citations). Her earlier PIRT framework laid the groundwork for deploying full robotic workloads on single-accelerator platforms. With a career spanning from networked control systems to modern heterogeneous computing, Liu’s research has garnered over 38 citations, establishing her as a key innovator in making autonomous robots practical for real-world, energy-constrained applications.

Research Focus

Key Achievements

3
H-Index
4
Papers
38
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Π-RT: A Runtime Framework to Enable Energy-Efficient Real-Time Robotic Vision Applications on Heterogeneous Architectures
19 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 14
🏛 Institutions: University of California System, Australian National University, University of Kaiserslautern

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago