Liting Niu
Papers
3
Total Citations
6
H-Index
2
About
Liting Niu is a researcher advancing the frontier of autonomous robotics through innovative hardware-software co-design and perceptual intelligence in Simultaneous Localization and Mapping (SLAM) systems. Her work focuses on making SLAM—a critical technology enabling robots to understand their position and environment—more accurate, energy-efficient, and perceptually rich. Niu’s major contributions include pioneering a hardware-software co-design approach for matrix-solving in nonlinear optimization SLAM, which addresses the computational bottlenecks of real-time robotic navigation. She also developed an energy-efficient FPGA accelerator for pose estimation in mobile V-SLAM robots, demonstrating how specialized hardware can enable real-time performance on power-constrained platforms. Most notably, Niu introduced LP-SLAM, a Language-Perceptive RGB-D SLAM system that integrates large language models to achieve semantic and text-level environmental understanding—a leap beyond traditional geometric mapping. Each of these first-author papers has garnered 2 citations, reflecting early recognition of their potential. By bridging algorithmic innovation with hardware acceleration and language-driven perception, Niu is shaping the next generation of autonomous systems that can not only navigate but also comprehend their surroundings.
Research Focus
Key Achievements
Top Papers
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