Papers
14
Total Citations
89
H-Index
5
About
Serban Olaru is a robotics and automation researcher whose work centers on robot kinematics, neural network control systems, and intelligent instrumentation for manipulator systems. His most significant contributions lie in solving the inverse kinematics problem — one of robotics' most computationally challenging tasks — through innovative assisted methods and neural network approaches. His 2014 paper on solving inverse kinematics using assisted research methods garnered 22 citations, while his development of the iterative pseudo-inverse Jacobian Neural Network Matrix technique, applied to controlling DC motors in manipulators, has proven particularly influential in achieving precise joint displacement control. Olaru has consistently championed the integration of LabVIEW instrumentation as both a simulation and optimization platform, demonstrating its utility across forward and inverse kinematics, dynamic behavior analysis, and robotic animation. His early work on magnetorheological dampers (2009) reveals a long-standing interest in improving robot dynamic stability. Collectively accumulating over 80 citations, his research portfolio reflects a career dedicated to bridging computational intelligence and practical robotics engineering, offering students and practitioners valuable tools for achieving extreme precision in multi-manipulator control environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2Assisted Research of the Neural Network13 citations · 2012
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- 5Animation in Robotics with LabVIEW Instrumentation6 citations · 2019
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- 8Research of the Neural Network by Back Propagation Algorithm4 citations · 2012
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