Papers
14
Total Citations
181
H-Index
7
About
Ehsan Zakeri is a robotics and control systems researcher whose work spans industrial robot control, vision-based servoing, and intelligent automation. His research career demonstrates a consistent focus on developing robust control architectures that bridge perception and physical interaction, particularly in challenging real-world environments characterized by model uncertainties and dynamic disturbances. Zakeri's most significant contributions center on cascade vision/force control frameworks for industrial robots, with his 2021 paper on continuous integral sliding-mode control accumulating 51 citations — his most impactful work to date. His early research explored fuzzy logic and PWM-based control for parallel robots (50 citations) and UAV path tracking, establishing a foundation in intelligent control methods. Over time, his focus evolved toward sophisticated sensor fusion approaches, incorporating photogrammetry sensors, adaptive neuro-PID methods, and robust Kalman filtering for precise end-effector pose estimation and dynamic path tracking. More recently, Zakeri has pioneered AI-driven robotic systems for medical applications, developing intelligent force control and deep-feature ultrasound image-based visual servoing for cardiac examination robots — a compelling translation of industrial control expertise into clinical robotics. With over 160 cumulative citations, his body of work reflects a meaningful trajectory from foundational control theory toward safety-critical, perception-driven autonomous robotic systems.
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