Papers
2
Total Citations
15
H-Index
2
About
Adrian Ghionea is a researcher focused on the intersection of neural networks, mobile robotics, and production system automation. His work primarily addresses the optimization of trajectory and guidance for mobile robots, with a key contribution being the development of online convergence methods that minimize the discrepancy between system output and target data. This approach, detailed in his most-cited paper "Assisted Research of the Neural Network" (2012, 13 citations), offers a pathway for real-time adaptive control without the need for extensive pre-programming. Ghionea has also explored the practical application of mobile robots in automated production systems, as seen in his 2011 work on tools to increase application efficiency (2 citations). By simulating robot movement and addressing logistical challenges, his research bridges theoretical neural network optimization with tangible improvements in industrial automation. While his citation counts are modest, Ghionea’s contributions are notable for their focus on practical, implementable solutions for modern production environments, making his work relevant for researchers and engineers seeking to enhance robotic efficiency in real-world systems.
Research Focus
Key Achievements
Top Papers
- 1Assisted Research of the Neural Network13 citations · 2012
- 2