Abdelbadiaa Chaker

Papers

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About

Abdelbadiaa Chaker is a researcher specializing in robotics, sensor fusion, and control systems, with a particular focus on enhancing the precision and reliability of manipulator technologies. His major contribution lies in advancing joint angle monitoring for serial manipulators, a critical area for industrial automation and robotic precision. In his most-cited work, "IMU Based Serial Manipulator Joint Angle Monitoring: Comparison of Complementary and Double Stage Kalman Filter Data Fusion" (2022), Chaker systematically compares two key data fusion techniques—complementary filters and double-stage Kalman filters—to improve the accuracy of inertial measurement unit (IMU) data in real-time robotic applications. This study provides a practical framework for engineers seeking robust, low-cost solutions for kinematic monitoring, directly impacting the development of more responsive and reliable robotic systems. While his citation count is still growing, Chaker’s work demonstrates a strong foundational contribution to sensor integration and state estimation, positioning him as an emerging voice in applied robotics. His research is particularly valuable for students and practitioners exploring efficient filtering methods for dynamic systems.