Papers

6

Total Citations

19

H-Index

3

About

Aditya Kurniawan is a robotics researcher specializing in sensor noise reduction, mobile robot navigation, and autonomous systems. His primary research focuses on mitigating structural noise in Kinect sensors—a critical challenge for spatial recognition in robotic vision. Kurniawan’s key contributions include developing the Isolated Neighborhood-Averaging Filter and the Saturated Iteration of Neighborhood Averaging Filter, algorithms designed to eliminate shadow artifacts and edge noise from Kinect depth data. These techniques enhance the reliability of visual sensors for robots like the Wild Thumper and ITIS mobile data collector. His work on Region of Interest (ROI)-based image quality assessment, using Structural Similarity Index (SSI), provides a targeted method for evaluating filtered image regions. Kurniawan’s papers have garnered citations from peers working on sensor calibration and robotic perception. Notably, he designed the Dagu RS003B75 chassis-based MINION robot, a prototype for intelligent mine detection and remote detonation, demonstrating applied defense robotics. His research bridges practical filtering algorithms and real-world mobile robot deployment, offering foundational techniques for students and engineers tackling sensor noise in autonomous navigation.

Research Focus

Key Achievements

3
H-Index
6
Papers
19
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Pengaruh Isolated Neighborhood-Averaging Filters Pada Kinect Structural Noise Sebagai Sistem Navigasi Robot Wild Thumper
4 citations · 2017
📈 Most Prolific Year: 2018 (3 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: State University of Malang, Universitas Internasional Semen Indonesia

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago