Yasaman Parandian
Papers
2
Total Citations
10
H-Index
2
About
Yasaman Parandian is a robotics researcher whose work focuses on the control, modeling, and intelligent interaction of autonomous systems, particularly flying and manipulative robots. Her key research areas include aerial robotics, control systems, and the application of artificial neural networks for real-time image processing. Parandian’s major contributions address two critical challenges in robotics: the need for rapid, precise positioning in dynamic environments and the demand for reliable, cost-effective simulation before physical deployment. Her 2015 paper on time-optimized digital image processing for a ball and plate system, which has garnered 5 citations, demonstrates how artificial neural networks can enable a robot controller to react swiftly to a moving object’s current position—a fundamental problem in robot-object interaction. In her 2016 work on an octorotor flying robot, also cited 5 times, she advanced the field by emphasizing the importance of software-in-the-loop simulation to predict flight behavior and ensure structural integrity before costly physical production. Parandian’s research is notable for bridging theoretical control design with practical implementation, offering students and researchers a clear pathway from simulation to real-world robotic performance.
Research Focus
Key Achievements
Top Papers
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- 2