Papers
7
Total Citations
81
H-Index
6
About
Artem Melnyk is a pioneering researcher in physical human-robot interaction, focusing on how robots can perceive and respond to human touch and social gestures. His work centers on three key areas: tactile sensing through artificial skin, adaptive robotic control, and biomimetic social interaction. Melnyk's most impactful contribution is his development of a touch-based admittance control system that uses neural learning to enable a robotic arm to adapt its compliance in four directions based on tactile input from artificial skin (19 citations). He has also made significant advances in understanding and replicating the human handshake, analyzing synchrony patterns through wavelet transforms and data gloves, and creating bio-inspired plastic controllers that allow robots to shake hands naturally (14 citations each). His innovative work extends to postural balance, where he designed a tensegrity-based vertebral column robot with synergistic neural control (14 citations). Melnyk has also contributed to accessible robotics through low-cost tactile sensor designs using Electrical Impedance Tomography, demonstrating his commitment to practical, scalable solutions for human-robot interaction.
Research Focus
Key Achievements
Top Papers
- 1
- 2Analysis of synchrony of a handshake between humans14 citations · 2014
- 3Bio-inspired plastic controller for a robot arm to shake hand with human14 citations · 2016
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- 7Analysis of a handshake between humans using wavelet transforms3 citations · 2015