Mubeen Akhtar
Papers
1
Total Citations
10
H-Index
1
About
Mubeen Akhtar is a researcher in robotics and embedded systems, with a focus on low-cost, intelligent control solutions for autonomous navigation. Her key contributions lie in the intersection of neural networks and microcontroller-based robotics, particularly in developing efficient obstacle avoidance systems. Her most cited work, "A low cost microcontroller implementation of neural network based hurdle avoidance controller for a car-like robot" (2010), demonstrates a practical approach to deploying a multilayer feed-forward neural network with backpropagation training on a single-chip 89C52 microcontroller. This offline-trained system enables a car-like robot to navigate around obstacles without expensive hardware, showcasing a cost-effective pathway for integrating AI into resource-constrained platforms. With 10 citations, this paper highlights her impact in making neural network control accessible for real-world robotic applications. Akhtar’s work is notable for bridging theoretical machine learning with embedded implementation, offering valuable insights for students and researchers in affordable robotics, autonomous systems, and embedded AI. Her research continues to inspire low-cost innovations in intelligent control.
Research Focus
Key Achievements
Top Papers
- 1