Liang Liu
Papers
4
Total Citations
13
H-Index
3
About
Liang Liu is a researcher whose work spans indoor localization, autonomous robotics, and embedded computer vision systems. With a career bridging multi-sensor fusion and intelligent navigation, Liu has made notable contributions to the development of robust localization frameworks that leverage diverse sensing modalities. Most prominently, Liu played a central role in creating the LuViRA Dataset — the Lund University Vision, Radio, and Audio dataset — a synchronized multisensory resource combining color images, depth maps, IMU readings, and 5G massive MIMO channel responses for accurate indoor localization. This dataset, cited across both its 2023 and 2024 releases, represents a significant infrastructure contribution to the localization research community. Earlier work on multi-robot exploration demonstrated Liu's longstanding interest in pose-independent map integration strategies for unknown environments. More recently, Liu has ventured into hardware-software co-design, contributing to a specialized VLIW vector processor architecture optimized for ORB feature extraction — a critical component in SLAM and augmented reality pipelines. Collectively, Liu's research reflects a sustained commitment to making autonomous systems more perceptually capable, efficient, and deployable in real-world environments, with growing recognition across robotics, signal processing, and computer architecture communities.
Research Focus
Key Achievements
Top Papers
- 1
- 2Integrating Line Segment Based Maps in Multi-Robots Exploration3 citations · 2009
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