Eka Samsul Ma’arif
Papers
1
Total Citations
4
H-Index
1
About
Eka Samsul Ma’arif is a researcher focused on robotics, automation, and manufacturing systems, with a particular emphasis on trajectory generation and computer vision for industrial applications. His most-cited work, "A Trajectory Generation Method Based on Edge Detection for Auto-Sealant Cartesian Robot" (2014, 4 citations), introduces an algorithm that uses captured images to generate precise trajectories for sealant processes in Cartesian robots. This contribution addresses a critical challenge in manufacturing: the need for adaptable, error-free automation across varying engine models. By enabling robots to detect edges and adjust paths autonomously, Ma’arif’s method enhances productivity, reduces human error, and saves time in production lines. His research bridges computer vision and robotics, offering practical solutions for real-world manufacturing efficiency. While his citation count is modest, his work holds significance for engineers and researchers in industrial automation, particularly those seeking to integrate vision-based systems into robotic tasks. Ma’arif’s contributions underscore the importance of adaptive algorithms in modern manufacturing, making his research a valuable reference for advancing smart factory technologies.
Research Focus
Key Achievements
Top Papers
- 1