Liling Ma
Papers
2
Total Citations
11
H-Index
2
About
Liling Ma is a researcher whose work lies at the intersection of robotics, intelligent control, and fault-tolerant systems. Ma’s key contributions focus on enhancing the reliability and autonomy of robotic platforms, particularly in challenging operational environments. A standout achievement is the development of a deep learning-based fault-tolerant control method for wheel-legged robots, which can simultaneously detect and manage multiple displacement sensor faults—a significant advance over traditional single-sensor approaches. This work, published in 2018, has garnered 8 citations and addresses a critical gap in robust robot control. More recently, Ma has contributed to the field of automated vehicle testing by designing a novel robotic driver equipped with adaptive PI controllers. These controllers, based on full form dynamic linearization (FFDL), enable precise speed tracking during vehicle tests, offering a universal and simple solution for automotive validation. With a growing citation record, Ma’s research demonstrates a clear trajectory toward creating more resilient and intelligent robotic systems, bridging the gap between theoretical control methods and practical, real-world applications in both mobile robotics and autonomous vehicle technology.
Research Focus
Key Achievements
Top Papers
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- 2