Umi Kalthum Ngah

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About

Umi Kalthum Ngah is a pioneering researcher in swarm robotics and autonomous surface vehicles (ASVs), with a focus on bio-inspired algorithms and practical calibration frameworks. Her work centers on developing cost-effective, scalable solutions for marine applications, addressing challenges such as complex instrument deployment and resource-intensive data collection. Ngah’s most notable contribution is the introduction of the Fly Optimization Algorithm (FOA), a novel bio-inspired approach designed for path planning in swarms of autonomous robots, initially targeting the localization of deepest underwater regions. She also developed Drosobots®, a swarm of mini ASVs, and established a calibration framework using virtual simulation software like Webots™ and controlled swimming pool environments. Her 2013 paper, “An introduction to swarming robotics: application development trends,” has garnered 10 citations, while her 2011 calibration framework paper has 9 citations, reflecting her foundational impact in the field. Ngah’s work bridges theoretical swarm intelligence with real-world marine robotics, offering practical pathways for deploying autonomous fleets in environmental monitoring and exploration. Her research continues to inspire advancements in low-cost, multi-robot systems for complex aquatic tasks.