Yuting Deng

Chengdu University of Technology

Papers

1

Total Citations

7

H-Index

1

About

Yuting Deng is a researcher in robotics and artificial intelligence, with a primary focus on simultaneous localization and mapping (SLAM) algorithms and their practical deployment in service robotics. Her most-cited work, "Application of Simultaneous Location and Map Construction Algorithms Based on Lidar in the Intelligent Robot Food Runner" (2021, 7 citations), addresses a critical challenge in the hospitality industry: making autonomous food delivery robots more accessible and cost-effective. By applying LiDAR-based SLAM to intelligent robot food runners, Deng demonstrates how advanced mapping and navigation techniques can be adapted for real-world, budget-constrained environments. This contribution not only advances the field of mobile robotics but also bridges the gap between high-end research and commercial viability. Deng’s work is notable for its emphasis on affordability and practical implementation, offering a pathway for smaller restaurants to adopt robotic solutions. Her research underscores the potential of SLAM algorithms to transform everyday service tasks, making her a promising voice in the intersection of robotics, AI, and applied engineering.

Research Focus

Key Achievements

1
H-Index
1
Papers
7
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Application of Simultaneous Location and Map Construction Algorithms Based on Lidar in the Intelligent Robot Food Runner
7 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Chengdu University of Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago