Ehsan Maani Miandoab

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About

Ehsan Maani Miandoab is a robotics researcher whose work bridges the gap between intelligent control systems and real-world industrial applications. His primary research areas include cable-driven parallel robots, computer vision for robotics, and dynamic parameter identification for manipulators. Maani Miandoab’s most notable contribution is a neural network-aided vision system for cable-driven parallel robots, which addresses the critical challenge of precise trajectory planning and control in flexible systems used for painting, rehabilitation, and 3D printing. This work has garnered 7 citations. He has also advanced the field of sports robotics through a comparative analysis of ball detection algorithms (6 citations), evaluating accuracy, robustness, and computational efficiency. Additionally, his experimental validation of parameter identification techniques for robot manipulators (5 citations) provides a practical solution for optimal path planning and collision avoidance in industrial settings, particularly when handling payloads with unknown physical properties. Maani Miandoab’s research is characterized by its direct applicability to automation challenges, making him a rising voice in the development of more adaptive and reliable robotic systems for manufacturing and service industries.