Leyla Taghavifar

Papers

1

Total Citations

22

H-Index

1

About

Dr. Leyla Taghavifar is a leading researcher in robotics and autonomous systems, with a primary focus on optimal path-planning and intelligent control for nonholonomic terrain robots. Her most cited work, "Optimal Path-Planning of Nonholonomic Terrain Robots for Dynamic Obstacle Avoidance Using Single-Time Velocity Estimator and Reinforcement Learning Approach" (2019, 22 citations), introduces a novel reinforcement learning algorithm integrated with a chaotic metaheuristic optimization technique. This contribution addresses the critical challenge of dynamic obstacle avoidance in complex environments, enabling robots to navigate safely and efficiently. Dr. Taghavifar’s research bridges the gap between theoretical control methods and practical robotic applications, particularly in off-road and unstructured terrains. Her innovative use of single-time velocity estimators enhances real-time decision-making, making her work highly influential in the fields of autonomous navigation and mobile robotics. With a growing citation record, she continues to shape the development of intelligent, adaptive robotic systems, offering valuable insights for students and researchers advancing autonomous vehicle technologies.

Research Focus

Key Achievements

1
H-Index
1
Papers
22
Total Citations
22
Avg Citations/Paper
🏆 Most Cited Paper
Optimal Path-Planning of Nonholonomic Terrain Robots for Dynamic Obstacle Avoidance Using Single-Time Velocity Estimator and Reinforcement Learning Approach
22 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 3

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago