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About

Marni Azira Markom is a robotics researcher whose work focuses on the foundational challenges of autonomous mobile robot navigation, particularly in the areas of environment mapping, localization, and sensor data processing. Her research addresses a critical question: how can a robot accurately know where it is and navigate through its surroundings, especially in noisy, real-world conditions. Her most cited work, "A mapping mobile robot using RP Lidar scanner" (2015, 35 citations), explores the use of LiDAR technology for environmental mapping, a cornerstone for applications ranging from autonomous navigation to search and rescue. Building on this, she has developed and refined localization algorithms, notably through her work on scan matching and KNN classification (2017, 11 citations), which improves a robot’s ability to determine its position. Markom has also tackled the practical problem of sensor noise, investigating laser range finder filters (2016) to ensure reliable data collection. Her more recent contribution, an improved KNN scan matching method (2019), directly addresses inaccuracies in the standard Iterative Closest Point (ICP) algorithm, offering a more robust solution for local map classification. Through this body of work, Markom has made tangible contributions to making mobile robots more reliable and autonomous in complex environments.