Pengjun Mao

Henan University of Science and Technology

Papers

4

Total Citations

19

H-Index

3

About

Pengjun Mao is a leading researcher at the intersection of aerial robotics and embodied intelligence, with a primary focus on the control and manipulation capabilities of unmanned aerial manipulators (UAMs). His groundbreaking work addresses the fundamental challenge of enabling flying robots to actively and safely interact with their environment. Mao has made significant contributions to robust control theory, notably developing a nonsingular global fast terminal sliding mode controller enhanced by an RBF neural network for precise trajectory tracking, and a composite control scheme with an extended state observer for regulating contact forces during physical interaction. These innovations are critical for deploying UAMs in dangerous or inaccessible tasks. Beyond aerial systems, his research extends to bio-inspired robotics, where his comparative gait analysis of goats on varying slopes has informed the design of more agile walking mechanisms. Most recently, Mao has contributed a comprehensive review of embodied grasping, exploring how pre-trained models can revolutionize robotic perception and interaction. With his most-cited works accumulating over a dozen citations, Mao’s research is steadily shaping the future of autonomous, physically interactive robots.

Research Focus

Key Achievements

3
H-Index
4
Papers
19
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
A Trajectory Tracking Approach for Aerial Manipulators Using Nonsingular Global Fast Terminal Sliding Mode and an RBF Neural Network
6 citations · 2022
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: Henan University of Science and Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago