Pengfei Ma
Papers
2
Total Citations
20
H-Index
2
About
Pengfei Ma is a researcher whose work bridges advanced optimization theory and robotic actuation systems. His primary research areas include circular cone programming, interior-point methods, and variable stiffness joint actuators for robotics. Ma’s major contribution lies in developing a polynomial-time interior-point method based on kernel functions for circular cone optimization—a framework particularly valuable for solving optimal design problems in multi-fingered robotic grasping. This work has garnered 12 citations and extends beyond traditional second-order cone programming, offering broader applicability. In robotics, Ma has advanced the dynamic modeling and control of antagonistic variable stiffness joint actuators (VSJA), achieving independent control of position and stiffness. His 2021 study, with 8 citations, demonstrates a VSJA capable of varying stiffness over a larger range than comparable actuators, a significant step toward safer, more adaptable human-robot interaction. By integrating optimization theory with practical robotic control, Ma’s work provides foundational tools for both computational efficiency and mechanical compliance, making his research highly relevant for students and engineers in robotics, control systems, and optimization.
Research Focus
Key Achievements
Top Papers
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