Papers
6
Total Citations
51
H-Index
5
About
Adytia Darmawan is a robotics researcher whose work centers on autonomous systems, quadruped locomotion, and computer vision for search-and-rescue applications. His most impactful contribution, a deep multilayer network for automatic gun turret targeting (19 citations), demonstrates expertise in integrating AI with military robotics. Darmawan has significantly advanced quadruped robot control, developing gait planning for stable movement on slopes and fuzzy logic-based balance control for stair climbing—critical for real-world deployment in disaster zones. His YOLO-based object detection system (10 citations) was designed specifically for the Indonesian Search And Rescue Robot Competition, enabling legged robots to autonomously locate victims and extinguish fires in simulated burning buildings. Additional work includes corner detection using 2D LIDAR for the Trinity College International Firefighting Robot Contest. Across his publications, Darmawan consistently addresses the core challenge of maintaining stability and perception in unstructured environments, with applications ranging from military targeting to civilian rescue robotics. His research portfolio reflects a practical, competition-driven approach to solving real-world locomotion and detection problems.
Research Focus
Key Achievements
Top Papers
- 1Deep multilayer network for automatic targeting system of gun turret19 citations · 2017
- 2
- 3Body Balancing Control for EILERO Quadruped Robot while Walking on Slope8 citations · 2019
- 4
- 5Quadruped Robot Balance Control For Stair Climbing Based On Fuzzy Logic5 citations · 2021
- 6Corner Detection with 2-D RPLIDAR to Detect Furniture on TCIFFRC Tracks2 citations · 2020