Hamed Safari Bidokhti
Papers
1
Total Citations
8
H-Index
1
About
Hamed Safari Bidokhti is a researcher whose work bridges robotics, artificial intelligence, and mechanical systems, with a particular focus on solving complex kinematic problems in parallel manipulators. His most-cited paper, "Direct kinematics solution of 3-RRR robot by using two different artificial neural networks" (2015), addresses one of the most challenging issues in robotics: the direct kinematics of parallel manipulators, which typically involves highly nonlinear equations with no straightforward analytical solution. By applying two distinct artificial neural network architectures, Bidokhti demonstrated how machine learning can effectively approximate these solutions, offering a practical alternative to traditional computational methods. This work, cited 8 times, highlights his contribution to integrating neural networks into robotic control and design. His research is particularly valuable for students and engineers working on parallel robots, where precision and real-time computation are critical. Bidokhti’s approach not only advances theoretical understanding but also provides tools for real-world applications in automation and manufacturing, making him a notable figure in the intersection of robotics and AI.
Research Focus
Key Achievements
Top Papers
- 1