SARA GHATTA
Papers
1
Total Citations
2
H-Index
1
About
Sara Ghatta is a researcher at the forefront of intelligent robotics and autonomous systems, with a primary focus on developing practical, neural-network-driven solutions for real-world vehicular automation. Her most cited work, "Automatic Robot Car Parallel Parking System Using Artificial Neural Network" (2024), has garnered 2 citations—a notable early impact for a recent publication. This contribution addresses a classic challenge in autonomous driving: enabling a robotic vehicle to execute precise parallel parking maneuvers without human intervention. By leveraging artificial neural networks, Ghatta’s system learns optimal steering and trajectory planning, moving beyond traditional rule-based algorithms to offer adaptive, robust performance in varied parking scenarios. Her research bridges the gap between theoretical machine learning and applied robotics, demonstrating how neural architectures can enhance spatial awareness and control in constrained environments. While her citation count is still growing, this work signals a promising trajectory in autonomous navigation and embedded AI systems. For students and researchers, Ghatta’s approach exemplifies how targeted, application-driven neural network design can solve complex, real-time control problems—a critical step toward fully autonomous urban mobility.
Research Focus
Key Achievements
Top Papers
- 1