Fauzy Satrio Wibowo
National Taipei University of Technology, State University of Malang
Papers
5
Total Citations
49
H-Index
3
About
Fauzy Satrio Wibowo is a researcher at the forefront of industrial robotics and human-robot collaboration, with a focus on energy efficiency and intelligent automation. His most impactful work, "BN-LSTM-based energy consumption modeling approach for an industrial robot manipulator" (2023, 31 citations), introduces a novel deep learning method that combines Bayesian Networks with Long Short-Term Memory networks to accurately predict and optimize energy use in robotic systems—a critical contribution to sustainable manufacturing. Wibowo also pioneered cost-effective vision systems for robotics, as demonstrated in his 2017 paper on integrating the Pixy CMUcam5 with the Bioloid robot for soccer-playing applications, making advanced perception accessible to low-budget platforms. His research on behavior analysis for human-robot collaboration (2022, 6 citations) uses intention graphs to enhance assembly task efficiency, bridging the gap between human operators and automated systems. Additionally, his work on photogrammetry for 3D surface reconstruction (2021) showcases versatility, applying computer vision to fields like archaeology and medicine. With a growing citation record and a focus on practical, scalable solutions, Wibowo is shaping the future of intelligent, energy-aware robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Integrating embedded color vision to Bioloid robot for playing soccer8 citations · 2017
- 3
- 4Development of Photogrammetry Application for 3D Surface Reconstruction2 citations · 2021
- 5