Zesu Cai

Harbin Institute of Technology

Papers

10

Total Citations

166

H-Index

6

About

Zesu Cai is a leading researcher in mobile robotics, with a primary focus on autonomous navigation, simultaneous localization and mapping (SLAM), and multi-robot coordination. His most influential work, "Robot path planning by leveraging the graph-encoded Floyd algorithm" (2021), has garnered 82 citations, demonstrating its significant impact on efficient path planning for robotic systems. Cai made foundational contributions to SLAM by introducing novel Rao-Blackwellized Particle Filters (RBPF) combined with unscented Kalman filters for monocular and stereo vision systems, enabling robust real-time mapping and localization in unknown environments. His early work on monocular vision-based navigation (2007, 28 citations) and multi-robot cooperative pursuit using task bundle auctions (2008, 16 citations) further established his expertise in intelligent, distributed robotic systems. Cai has also advanced practical applications, including odometric error modeling for precise pose tracking and GPRS-based guard robot alarm systems. With a career spanning foundational SLAM theory to applied multi-robot coordination, Cai’s research continues to influence autonomous navigation, cooperative robotics, and real-world robotic deployment.

Research Focus

Key Achievements

6
H-Index
10
Papers
166
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Robot path planning by leveraging the graph-encoded Floyd algorithm
82 citations · 2021
📈 Most Prolific Year: 2007 (2 Papers)
🤝 Key Collaborators: 20
🏛 Institutions: Harbin Institute of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago