Petrus Fajar Subekti
Papers
1
Total Citations
2
H-Index
1
About
Petrus Fajar Subekti is a robotics researcher whose work centers on machine vision and human-robot interaction, with a particular focus on enabling autonomous systems to perceive and interpret their environments. His most cited paper, "Design and implementation of machine vision for board game in lumen social robot system" (2014), demonstrates a foundational contribution: applying machine vision to the humanoid robot Nao, treating the camera system as an analog to biological eyes. Subekti’s research emphasizes that successful machine vision depends critically on the interpretation process—transforming raw visual data into actionable information for decision-making. This work, which has garnered 2 citations, showcases his ability to bridge theoretical computer vision with practical robotic applications, such as enabling a robot to play board games. By integrating perception with action, Subekti advances the field of social robotics, where robots must understand dynamic environments to interact naturally with humans. His contributions highlight the importance of robust visual interpretation in autonomous systems, laying groundwork for more intuitive and capable robotic assistants.
Research Focus
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Top Papers
- 1