Erich Potrich
Papers
1
Total Citations
15
H-Index
1
About
Erich Potrich’s research lies at the intersection of intelligent automation and industrial efficiency, with a primary focus on deep learning, machine vision, and robotic control systems. His most-cited work, "Optimization of Sorting Robot Control System Based on Deep Learning and Machine Vision" (2022, 15 citations), addresses a critical challenge in coal processing: replacing manual sorting in coal washing plants with automated, machine-driven dry separation. Potrich’s key contribution involves a comparative analysis of traditional PID controllers and dynamic domain fuzzy self-tuning PID algorithms, demonstrating how the latter significantly improves the precision of robotic grasping—determining optimal position and orientation for handling coal gangue. This work not only advances control theory but also offers a practical, scalable solution for reducing human labor and enhancing safety in harsh industrial environments. By integrating machine vision with adaptive control, Potrich’s research bridges the gap between theoretical optimization and real-world application, making a tangible impact on sustainable mining practices. His findings serve as a valuable reference for engineers and researchers developing intelligent sorting systems, highlighting the potential of deep learning to transform traditional manufacturing and resource recovery processes.
Research Focus
Key Achievements
Top Papers
- 1