Yudha Satya Perkasa
Papers
1
Total Citations
2
H-Index
1
About
Yudha Satya Perkasa is a researcher specializing in robotics, control systems, and intelligent computational modeling. His work focuses on improving robotic motion prediction and control through the integration of mathematical modeling and adaptive learning systems. In his most-cited paper, "Determining the arm's motion angle using inverse kinematics models and adaptive neuro-fuzzy interface system" (2021), Perkasa addresses a critical challenge in robotics: accurately predicting and controlling a robot arm’s movement. By combining inverse kinematics with an adaptive neuro-fuzzy inference system (ANFIS), he developed a method that enhances motion angle determination, bridging the gap between rigid mathematical equations and flexible learning-based logic. This contribution is vital for advancing autonomous robotic systems, particularly in precision tasks. Although his citation count is currently modest, his work lays foundational groundwork for more responsive and intelligent robotic control. Perkasa’s research is especially relevant for students and engineers exploring the intersection of robotics, fuzzy logic, and neural networks, offering a practical approach to making robots more adaptive and efficient in real-world applications.
Research Focus
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Top Papers
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