Zhen Zhou

Qingdao University, Jinan University

Papers

2

Total Citations

10

H-Index

2

About

Zhen Zhou is a pioneering researcher whose work bridges robotics and environmental analytical chemistry. In robotics, Zhou is best known for developing the FMI-EKF-SLAM algorithm (2020, 6 citations), a multi-innovation with forgetting factor approach that addresses the critical error accumulation problem in Extended Kalman Filter-based simultaneous localization and mapping. This contribution has provided a more robust solution for mobile robot navigation in complex, dynamic environments. More recently, Zhou has made significant strides in environmental monitoring, introducing an innovative dual-channel analytical system (2024, 4 citations) that combines double robotic sample preparations with mono and comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry. This system enables the online sequential analysis of volatile and semivolatile organic compounds in water matrices, offering unprecedented speed and sensitivity for detecting water contaminants. Zhou’s interdisciplinary work demonstrates a rare ability to apply advanced robotic automation to solve pressing environmental challenges. With a growing citation record and a portfolio that spans fundamental robotics algorithms to applied environmental sensing, Zhou is establishing a reputation for impactful, cross-domain research that promises to influence both autonomous systems and water quality monitoring.

Research Focus

Key Achievements

2
H-Index
2
Papers
10
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
A multi-innovation with forgetting factor based EKF-SLAM method for mobile robots
6 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: Qingdao University, Jinan University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago