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About

Moustafa M. Kurdi is a leading researcher in cooperative robotics, specializing in the intelligent coordination of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) for autonomous navigation and mission-critical applications. His most influential work, "Proposed system of artificial Neural Network for positioning and navigation of UAV-UGV" (20 citations), introduces a novel neural network system that fuses GPS, robot vision, and quadcopter sensor data to enable safe, adaptive path planning in unstructured environments. Kurdi’s broader research portfolio—spanning agricultural robotics, landmine detection, and efficient guidance systems—demonstrates a consistent focus on real-time obstacle avoidance and optimized trajectory control. His 2017 paper on quadcopter-UGV cooperation (5 citations) advances probabilistic roadmap methods for heterogeneous robot teams, while his 2022 work on agricultural robot motion planning (5 citations) integrates scanning, obstacle avoidance, and image processing for precision farming. Kurdi’s contributions to the Quadcopter Mobile Robotic System (QMRS) and his application of fuzzy logic and the Traveling Salesman Problem for autonomous path control highlight his commitment to practical, deployable solutions. With a career dedicated to bridging aerial and ground robotics, Kurdi’s research continues to shape the future of autonomous systems in defense, agriculture, and exploration.