Yekkehfallah Majid

Ministry of Education of the People's Republic of China, Xi'an Jiaotong University

Papers

Total Citations

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About

Majid Yekkehfallah is a robotics researcher specializing in autonomous navigation, sensor fusion, and human-robot interaction. His work centers on solving critical challenges in mobile robot localization and teleoperation, particularly for industrial and hazardous environments. His most cited paper, "Accurate 3D Localization Using RGB-TOF Camera and IMU for Industrial Mobile Robots" (2021, 10 citations), tackles the failure of visual localization in fast motion and low-texture settings by fusing RGB-TOF camera data with inertial measurements, offering a robust solution for automated vehicles. Earlier, Yekkehfallah compared Extended Kalman Filter (EKF) and Sigma-Point Kalman Filter (SPKF) algorithms for Simultaneous Localization and Mapping (SLAM) (2017, 2 citations), providing insights into handling noisy sensor data for accurate path detection. He also advanced teleoperation safety with "Safety on Teleoperation Demining wheeled robots based on fuzzy logic controller and haptic system" (2017, 2 citations), integrating fuzzy logic and haptic feedback to reduce operator errors in urgent demining scenarios. With a focus on practical, real-world applications, Yekkehfallah’s contributions enhance the reliability and safety of autonomous and remotely operated robots, making his work valuable for researchers in field robotics and human-robot systems.