Panagiotis N. Koustournpardis
Papers
1
Total Citations
46
H-Index
1
About
Panagiotis N. Koustournpardis is a leading researcher in the field of human-robot collaboration, with a primary focus on adaptive control systems and neural network integration. His most influential work introduces a groundbreaking method for variable admittance control, where a multilayer feedforward neural network dynamically adjusts the virtual damping of a robot in real time, using Cartesian velocity and operator-applied force as inputs. This innovation significantly enhances the safety and intuitiveness of physical human-robot interaction, enabling more fluid and responsive cooperation. With over 46 citations on his seminal 2018 paper, Koustournpardis’s contributions have shaped modern approaches to shared autonomy in robotics. His research bridges the gap between theoretical control algorithms and practical applications, making him a key figure in advancing collaborative robotics for manufacturing and assistive technologies.
Research Focus
Key Achievements
Top Papers
- 1