Yasheerah Yaqoot
Papers
3
Total Citations
26
H-Index
2
About
Yasheerah Yaqoot is an emerging researcher at the forefront of autonomous aerial robotics and intelligent multi-agent systems, with a focus on integrating large language models and vision-language models (VLMs) into real-world robotic navigation. Her most influential work, "UAV-VLA: Vision-Language-Action System for Large Scale Aerial Mission Generation" (2025), has already garnered 22 citations, demonstrating rapid recognition within the robotics and AI communities. This system represents a significant advance in human-robot communication, enabling users to generate complex aerial flight paths by combining satellite imagery with GPT-powered reasoning. Yaqoot's research extends beyond single-agent systems — her work on "ImpedanceGPT" and "SwarmVLM" addresses the considerably harder problem of coordinating heterogeneous robot swarms, including UAV-AGV collaborations, in dynamic and unpredictable environments such as warehouses shared with humans. By embedding impedance control within VLM-guided frameworks, she bridges high-level AI reasoning with low-level physical safety — a rare and valuable intersection. Though early in her career, Yaqoot's cumulative impact of 26 citations across three 2025 publications marks her as a promising voice in next-generation autonomous systems research.
Research Focus
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Top Papers
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