Mohamad Iskandar Petra

About

Mohamad Iskandar Petra is a researcher at the forefront of intelligent robotics and manufacturing systems, with a particular focus on integrating machine learning into real-world industrial applications. His work bridges the gap between theoretical AI models and practical hardware implementation, especially in robotic arm control and condition monitoring. Petra's most-cited paper, "Use of machine learning models in condition monitoring of abrasive belt in robotic arm grinding process" (2024, 27 citations), addresses a critical challenge in automated manufacturing: predicting abrasive belt wear to ensure product integrity and process efficiency. By applying machine learning to this problem, he has contributed to more reliable and autonomous robotic grinding systems. Earlier, Petra demonstrated his expertise in hardware-software co-design with "Implementation of Folding Architecture Neural Networks into an FPGA for an Optimized Inverse Kinematics Solution of a Six-Legged Robot" (2013, 6 citations), where he tackled the memory and computational constraints of embedded systems. This work showcases his ability to optimize complex robotic algorithms for deployment on resource-limited hardware. Through his research, Petra is advancing the next generation of intelligent, self-monitoring robotic systems for manufacturing.

Research Focus

Key Achievements

Top Papers

1. 1
   Use of machine learning models in condition monitoring of abrasive belt in robotic arm grinding process

   27 citations · 2024
2. 2
   Implementation of Folding Architecture Neural Networks into an FPGA for an Optimized Inverse Kinematics Solution of a Six-Legged Robot

   6 citations · 2013

Key Collaborators

Contact & Links