Joshua C. Triyonoputro
Papers
8
Total Citations
126
H-Index
5
About
Joshua C. Triyonoputro is a robotics researcher specializing in autonomous industrial assembly, with a particular focus on solving the challenging problem of peg-in-hole insertion under uncertainty. His most influential work, "Quickly Inserting Pegs into Uncertain Holes using Multi-view Images and Deep Network Trained on Synthetic Data" (62 citations), demonstrates a novel approach that combines multiple in-hand cameras, force-torque sensing, and deep learning trained entirely on synthetic data to enable robots to reliably assemble parts on surfaces with varying colors and textures. Triyonoputro was a key member of Team O2AS, which competed in the World Robot Summit 2018 Assembly Challenge, and his co-authored paper on lessons from that competition (26 citations) has become a reference for the field. He has also contributed innovative gripper designs, including a bio-inspired double-jaw hand modeled after the moray eel’s pharyngeal jaw, and a compact dual-gripper mechanism for multi-object assembly. His work bridges perception, control, and mechanical design to push the boundaries of autonomous manufacturing, making him a notable figure in robotic assembly research.
Research Focus
Key Achievements
Top Papers
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- 6A Double Jaw Hand Designed for Multi-Object Assembly4 citations · 2018
- 7A Double-jaw Hand that Mimics A Mouth of the Moray Eel3 citations · 2018
- 8A Double Jaw Hand Designed for Multi-object Assembly2 citations · 2018