Zhengda Wu

PLA Academy of Military Science

Papers

1

Total Citations

2

H-Index

1

About

Zhengda Wu is a researcher specializing in real-time systems, particularly the scheduling and response-time analysis of robotic middleware. His work focuses on enhancing the predictability and performance of ROS2 (Robot Operating System 2), a critical framework for autonomous systems. Wu’s major contribution lies in his 2024 paper, “Deadline-Driven Enhancements and Response Time Analysis of ROS2 Multi-threaded Executors,” which addresses a key challenge in real-time robotics: ensuring that time-sensitive tasks meet their deadlines in multi-threaded execution environments. By proposing novel scheduling enhancements and rigorous analytical models, he provides a foundation for safer and more reliable autonomous systems, from self-driving cars to industrial robots. Though his most-cited work is recent, with 2 citations, its impact is already evident in the growing community of researchers and engineers seeking to harden ROS2 for safety-critical applications. Wu’s research bridges theoretical real-time scheduling with practical system design, offering tools and insights that enable developers to reason about timing guarantees in complex, concurrent robotic platforms. His work is essential reading for anyone building or analyzing real-time robotic systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Deadline-Driven Enhancements and Response Time Analysis of ROS2 Multi-threaded Executors
2 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: PLA Academy of Military Science

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago