Asma Jabeen

Papers

Total Citations

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About

Asma Jabeen is a researcher whose work lies at the intersection of autonomous robotics and intelligent fault detection systems. Her primary research focuses on enhancing the reliability and autonomy of robotic navigation through innovative sensor data analysis. In her most cited work, "Fault Detection Using Sensors Data Trends for Autonomous Robotic Mapping" (2019), Jabeen introduced a novel approach to map building by analyzing qualitative trends from IMU and odometry sensor data streams. This contribution addresses a critical challenge in robotics: ensuring that autonomous systems can not only perceive their environment but also detect and recover from sensor faults in real time. While her citation count is still growing—with 2 citations for this key paper—her work represents an important step toward more resilient and self-correcting robotic systems. Jabeen's research is particularly valuable for students and engineers working on autonomous navigation, sensor fusion, and system reliability, as it bridges the gap between raw sensor data and actionable insights for fault-tolerant mapping. Her focus on qualitative trend analysis offers a practical framework for improving robotic autonomy in dynamic environments.