Tito Pradhono Tomo
Papers
28
Total Citations
734
H-Index
12
About
Tito Pradhono Tomo is a robotics researcher whose work centers on tactile sensing, soft skin sensors, and robotic manipulation. He is perhaps best known for developing the **uSkin** series of sensors — compact, soft, distributed 3-axis force-sensitive electronic skins designed for integration on robot hands. His 2017 paper introducing uSkin coverage for robot fingertips has accumulated 167 citations, while a 2018 follow-up detailing its integration on the humanoid robot iCub garnered 144 citations, reflecting the broad influence of this technology across the robotics community. His foundational work on Hall effect-based skin sensors, beginning in 2015 and elaborating through 2016, established key design principles — combining softness, digital output, and multi-axis force measurement — that underpin his later systems. Beyond hardware, Tomo has made significant contributions to perception and learning, developing CNN-based architectures for grasp stability prediction, slip detection using multimodal vision and touch, and ensemble learning frameworks for grasping state classification. His wearable fingertip sensor for capturing human force data further bridges human demonstration and robot imitation learning. Collectively, his portfolio — spanning sensor design, humanoid integration, and intelligent manipulation — positions him as a versatile and impactful contributor to the field of robotic tactile intelligence.
Research Focus
Key Achievements
Top Papers
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- 3Design and Characterization of a Three-Axis Hall Effect-Based Soft Skin Sensor106 citations · 2016
- 4A modular, distributed, soft, 3-axis sensor system for robot hands57 citations · 2016
- 5Detection of Slip from Vision and Touch34 citations · 2022
- 6Development of a hall-effect based skin sensor26 citations · 2015
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- 10A Wearable Three-Axis Tactile Sensor for Human Fingertips18 citations · 2018