Shujuan Yin

Baotou Teachers College

Papers

1

Total Citations

11

H-Index

1

About

Shujuan Yin is a researcher at the forefront of robotics and embedded systems, with a primary focus on energy-efficient hardware acceleration for autonomous navigation. Her most notable contribution is the development of an FPGA-based DS-SLAM accelerator, which enables mobile robots to perform Simultaneous Localization and Mapping (SLAM) in dynamic environments while dramatically reducing power consumption. This work, cited 11 times, addresses a critical bottleneck in real-world robotics: the computational intensity of fusing semantic information with traditional SLAM algorithms. By offloading processing to reconfigurable hardware, Yin’s design allows robots to not only localize and map but also understand dynamic objects in their surroundings—a key step toward truly autonomous systems. Her research bridges the gap between algorithmic innovation and practical deployment, making robots more efficient and responsive. Yin’s contributions are particularly impactful for mobile robotics, where battery life and real-time performance are paramount. Her work continues to inspire advances in hardware-software co-design for intelligent autonomous systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
11
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
An FPGA Based Energy Efficient DS-SLAM Accelerator for Mobile Robots in Dynamic Environment
11 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Baotou Teachers College

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago