Maha Salman

Egypt-Japan University of Science and Technology

Papers

Total Citations

H-Index

About

Maha Salman is a roboticist specializing in autonomous aerial manipulation and hybrid ground-aerial systems. Her research focuses on vision-based control for quadrotor manipulation, addressing the critical challenge of automating pick-and-place operations in hazardous environments where human teleoperation is too slow or imprecise. By integrating computer vision with flight control, Salman’s work enables drones to autonomously detect, grasp, and transport objects—paving the way for applications in disaster response, infrastructure inspection, and logistics. Her 2018 paper on vision-based quadrotor control (2 citations) and 2020 study on securing and transformation mechanisms for hybrid ground-aerial robots (2 citations) demonstrate her foundational contributions to designing versatile robots that can transition between rolling and flying modes. While her citation counts are modest, her research addresses a critical bottleneck in practical drone deployment: reliable autonomy in unstructured settings. Salman’s work is particularly notable for bridging the gap between theoretical control systems and real-world robotic functionality, offering a blueprint for next-generation robots that combine mobility, manipulation, and adaptive transformation.