Papers

2

Total Citations

14

H-Index

2

About

Azad R. Kareem is a researcher specializing in robotics, control systems, and sensor fusion, with a focus on improving the precision and reliability of robotic motion and navigation. His major contributions include pioneering work on inverse kinematics for robot manipulators, where he proposed a multi-neural network structure to significantly reduce positioning errors that arise when using a single network. This approach, detailed in his most-cited paper (9 citations), offers a robust solution for end-effector position control. In mobile robotics, Kareem advanced position measurement techniques by developing a modified Kalman Filter that integrates accelerometer and wheel encoder data. His 2022 study (5 citations) demonstrates how this sensor fusion method compensates for accelerometer drift, achieving stable and accurate localization over short periods. By addressing fundamental challenges in robotic positioning and estimation, Kareem’s work has practical implications for autonomous navigation and industrial automation. His research continues to influence the development of more reliable and error-tolerant robotic systems, making him a notable contributor to the fields of mechatronics and intelligent control.

Research Focus

Key Achievements

2
H-Index
2
Papers
14
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Inverse Kinematics Solution of Robot Manipulator End- Effector Position Using Multi-Neural Networks
9 citations · 2016
📈 Most Prolific Year: 2016 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Systems Control (United States), University of Technology - Iraq

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago