Ii Munadhif
Papers
2
Total Citations
42
H-Index
2
About
Ii Munadhif is a researcher focused on robotics, specifically the control and manipulation of robotic arms. His work integrates artificial intelligence to solve complex kinematic problems, most notably demonstrated in his highly cited 2016 paper on implementing a neural network for the inverse kinematic model of a 3-DOF arm drawing robot. This research, which has garnered 39 citations, showcases how artificial neural networks can effectively compute the joint angles required for precise robotic arm movement, a fundamental challenge in the field. Munadhif has also explored the classification of arm muscle signals for controlling manipulator robots using Support Vector Machines, as seen in his 2019 publication. By bridging machine learning with mechanical design, his contributions provide practical pathways for developing more intuitive and autonomous robotic systems, particularly for tasks requiring high precision or operation in hazardous environments. His work is a valuable resource for students and researchers interested in the intersection of neural networks, kinematics, and robotic control.
Research Focus
Key Achievements
Top Papers
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