Papers

9

Total Citations

84

H-Index

5

About

Zhengguang Ma’s research focuses on intelligent mobile robotics, with key contributions in path planning, multi-robot coordination, and sensor fusion for complex and hazardous environments. Ma is best known for developing a fusion approach that combines an improved A* algorithm with an adaptive Dynamic Window Approach (DWA), enabling mobile robots to navigate dynamically and avoid obstacles in real time—a method that has garnered 30 citations. Their work on a ROS-based multi-robot system simulator (28 citations) provides a seamless bridge between simulation and hardware experimentation, advancing the study of coordinated swarm behavior. Ma has also pioneered the integration of micro-ROS with resource-constrained microcontrollers for 2D mapping, and designed specialized robots for radioactive source detection and disposal, incorporating Lidar-depth camera fusion and neural network PID control to enhance precision and safety in nuclear environments. With notable achievements in both theoretical algorithm design and practical robotic systems, Ma’s research has significant implications for autonomous navigation, hazardous material handling, and multi-agent systems, making their work essential reading for students and researchers in robotics and control engineering.

Research Focus

Key Achievements

5
H-Index
9
Papers
84
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
A Fusion Approach for Mobile Robot Path Planning Based on Improved A* Algorithm and Adaptive Dynamic Window Approach
30 citations · 2021
📈 Most Prolific Year: 2020 (4 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: Shandong Academy of Sciences, Qilu University of Technology, Shandong Institute of Automation

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago