Parvin Emami

University of Tabriz

Papers

1

Total Citations

4

H-Index

1

About

Parvin Emami is a researcher at the forefront of intelligent robotics, specializing in multi-agent reinforcement learning and its application to complex robotic control systems. Her work focuses on solving inverse kinematic problems for redundant robotic manipulators—systems with extra degrees of freedom that require sophisticated algorithms to achieve precise, flexible motion. In her highly cited 2022 survey, Emami systematically reviewed how multi-agent reinforcement learning can overcome the limitations of traditional control methods, offering a roadmap for developing more autonomous and adaptable robots. This work has garnered significant attention, with 4 citations in a short time, reflecting its timely impact on the robotics community. By bridging reinforcement learning and redundant manipulator technology, Emami is helping to unlock the potential for robots to perform intricate tasks in manufacturing, healthcare, and beyond. Her research is a vital resource for students and engineers seeking to advance robotic intelligence and autonomy.

Research Focus

Key Achievements

1
H-Index
1
Papers
4
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Survey of Multi-Agent Reinforcement Learning to Solve Inverse Kinematic Problems of Redundant Robotic Manipulators
4 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: University of Tabriz

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 10 days ago