Amin Panah
Papers
1
Total Citations
3
H-Index
1
About
Amin Panah is a researcher in robotics and autonomous systems, with a primary focus on advancing Simultaneous Localization and Mapping (SLAM) for mobile robots. His most cited work, "Enhanced SLAM for Autonomous Mobile Robots using Unscented Kalman Filter and Neural Network" (2015), introduces a novel approach that integrates an optimized Unscented Kalman Filter (UKF) with a Radial Basis Function (RBF) neural network. This method significantly reduces SLAM errors in unknown indoor environments, improving the accuracy and robustness of autonomous robot navigation. By combining probabilistic filtering with machine learning, Panah addresses critical challenges in real-time robot localization and mapping. Although his citation count is modest—with this key paper garnering 3 citations—his work represents a meaningful contribution to the field, particularly in the integration of neural networks with traditional SLAM algorithms. Panah’s research is valuable for students and engineers exploring hybrid approaches to autonomous navigation, offering a foundation for further innovation in robotics and artificial intelligence.
Research Focus
Key Achievements
Top Papers
- 1