Papers

1

Total Citations

18

H-Index

1

About

Ruozhu Wu is a researcher at the forefront of autonomous robotics and intelligent motion planning, with a focus on enhancing the reliability and efficiency of mobile robots in real-world environments. Wu’s most notable contribution is the development of a Robust Reference Path Selection Method (RPSM), introduced in a 2022 paper that has garnered 18 citations. This method addresses a critical challenge in autonomous navigation—selecting optimal reference paths for patrol robots—by maintaining a dynamic array of path candidates that adapts to changing conditions. By integrating RPSM into existing motion planning algorithms, Wu’s work significantly improves the mobile performance and robustness of autonomous systems, enabling safer and more reliable operation in complex settings. This achievement underscores Wu’s commitment to bridging theoretical algorithms with practical deployment, making a tangible impact on the field of robotics. With a growing citation record, Wu’s research continues to influence advancements in path planning, autonomous navigation, and intelligent control, marking them as a promising contributor to the next generation of autonomous technologies.

Research Focus

Key Achievements

1
H-Index
1
Papers
18
Total Citations
18
Avg Citations/Paper
🏆 Most Cited Paper
A Robust Reference Path Selection Method for Path Planning Algorithm
18 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: State Key Laboratory of Industrial Control Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago