Yushi Guo
Papers
2
Total Citations
4
H-Index
2
About
Yushi Guo is a researcher at the forefront of embedded computer vision and autonomous navigation, specializing in energy-efficient hardware acceleration for visual odometry (VO) and simultaneous localization and mapping (SLAM). Their major contributions include the development of a groundbreaking single-frame bundle adjustment hardware accelerator, detailed in their 2025 paper, which achieves an impressive 197 μJ per frame—a critical advancement for power-constrained mobile platforms like drones and augmented reality devices. This work directly addresses the computational bottleneck of bundle adjustment in high-frame-rate VO, enabling real-time, low-power operation. Guo has also advanced the field of language-perceptive robotics with their 2023 work on LP-SLAM, integrating large language models (LLMs) into RGB-D SLAM systems to achieve semantic and text-level environmental understanding, pushing beyond traditional geometric mapping. With emerging citations totaling 4 across these key papers, Guo’s research is gaining traction for its practical impact on robot navigation, VR, and autonomous systems. Their work bridges the gap between efficient hardware design and intelligent perception, marking them as a rising innovator in mobile robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2