Papers
2
Total Citations
9
H-Index
2
About
Zihan Ma is a researcher whose work bridges robotics and cybersecurity, with a primary focus on quadruped robot locomotion and industrial robot system security. In their foundational 2020 study on gait planning, Ma analyzed Hopf oscillator dynamics to develop Central Pattern Generator (CPG) control networks for quadruped robots, constructing and modeling two distinct CPG architectures that demonstrated the feasibility of bio-inspired gait generation. This work, which has garnered 6 citations, provides a theoretical framework for stable, adaptive locomotion in legged robots. More recently, Ma has ventured into the critical domain of industrial robot safety with their 2024 paper introducing FuzzAGG, a fuzzing-driven attack graph generation framework. This innovative approach addresses the growing vulnerability of industrial robot systems to cyber threats, offering a systematic method to identify and visualize potential attack vectors. With 3 citations already, this work signals Ma’s expanding impact at the intersection of robotics and cybersecurity. Their research trajectory—from foundational locomotion algorithms to applied security frameworks—demonstrates a versatile and forward-thinking approach to solving real-world challenges in autonomous systems.
Research Focus
Key Achievements
Top Papers
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