Neda Daei -
Papers
1
Total Citations
6
H-Index
1
About
Neda Daei’s research lies at the intersection of robotics, artificial intelligence, and autonomous navigation, with a particular focus on enabling service robots to operate intelligently in dynamic indoor environments. Her most-cited work, “Service Robot Navigation Based on Q-Learning and Fuzzy Logic” (2011), introduces a novel hybrid approach that combines reinforcement learning with fuzzy decision-making, allowing robots—such as nurse or reception bots—to adapt their movement in semi-structured spaces. This contribution addresses a critical challenge in service robotics: balancing real-time adaptability with reliable path planning. With 6 citations, the paper has influenced subsequent studies in robot learning and control. Daei’s work is notable for bridging classical fuzzy logic with modern machine learning techniques, offering a practical framework that remains relevant as service robots become more common in healthcare and hospitality. Her research continues to inspire engineers and researchers seeking robust, learning-based solutions for real-world robot navigation.
Research Focus
Key Achievements
Top Papers
- 1Service Robot Navigation Based on Q-Learning and Fuzzy Logic6 citations · 2011