Papers

3

Total Citations

52

H-Index

3

About

Pengcheng Zheng is a rising star in multi-robot perception and cooperative localization, whose work addresses fundamental challenges in autonomous systems operating without external infrastructure. His primary research focuses on range-aided cooperative localization, multi-robot relative positioning, and multi-sensor calibration for robust state estimation. Zheng’s most impactful contribution is his 2022 paper on a multi-robot relative positioning and orientation system using UWB range measurements and graph optimization, which has garnered 39 citations and provides a practical solution for teams of robots to determine each other’s positions without GPS. Building on this, his 2023 work on drift-free cooperative localization and consistent dense reconstruction tackles the critical problem of maintaining accurate relative poses when robots lack overlapping fields of view—a common limitation in traditional loop-closure methods. Zheng also developed FDO-Calibr, a frequency-domain optimization approach for visual-aided IMU calibration that improves the reliability of visual-inertial odometry systems. His research is particularly notable for enabling fast, flexible, and consistent multi-robot reconstruction, making it highly relevant for search-and-rescue, warehouse automation, and environmental monitoring applications.

Research Focus

Key Achievements

3
H-Index
3
Papers
52
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Multi-robot relative positioning and orientation system based on UWB range and graph optimization
39 citations · 2022
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: University of Chinese Academy of Sciences, Chinese Academy of Sciences

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago