Mohammad Salah

Paderborn University, Hashemite University

Papers

Total Citations

H-Index

About

Mohammad Salah is a robotics researcher whose work bridges the critical gap between machine perception and autonomous mobility. His primary research areas include visual attention modeling for robotic systems, nonholonomic mobile robot control, and the complex dynamics of skid-steered tracked vehicles. Salah’s most influential contribution, “Evaluation of Visual Attention Models for Robots” (2006, 24 citations), introduced a pioneering approach that processes image regions rather than individual pixels, enabling significantly faster visual attention in robot vision systems—a breakthrough for real-time applications. His subsequent work on motion control has been equally impactful, with studies like “Tracking Control for a Two-Wheel Differentially Driven Nonholonomic Mobile Robot” (2022, 9 citations) and “Controlling a Skid-Steered Tracked Mobile Robot with Slippage Using Various Control Schemes” (2019, 9 citations) addressing the notoriously difficult challenge of managing track-terrain interactions and slippage. Salah’s research is characterized by its practical focus on overcoming real-world constraints in robotic locomotion and perception, making his findings valuable for engineers developing robust autonomous systems in unstructured environments.