Rasul Fesharakifard
Papers
13
Total Citations
105
H-Index
4
About
Rasul Fesharakifard’s research bridges industrial automation and human-robot interaction, with a focus on robotic welding, exoskeletons, and mobile robot navigation. His most cited work, “Precise seam tracking in robotic welding by an improved image processing approach” (39 citations), introduces a vision-based method that significantly enhances weld path accuracy, addressing a critical challenge in manufacturing. In rehabilitation robotics, his “novel hand exoskeleton to enhance fingers motion for tele-operation of a robot gripper with force feedback” (22 citations) integrates haptic feedback, enabling intuitive remote manipulation—a contribution with implications for both assistive technology and hazardous environment operations. Fesharakifard has also advanced path planning with an adaptive genetic algorithm-potential field hybrid (13 citations) and explored SLAM-based localization for differential drive robots. His work on force-sensitive grippers and model predictive control for cable robots further demonstrates versatility across robotic systems. With over 100 total citations, his research is characterized by practical, sensor-driven solutions that improve precision and safety in real-world robotic applications.
Research Focus
Key Achievements
Top Papers
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- 7Updating LQR Control for Full Dynamic of a Quadrotor3 citations · 2017
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