Demonstration: Minsight - A Soft Vision-Based Tactile Sensor for Robotic Fingertips
2024
Miscellaneous
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Beyond vision and hearing, tactile sensing enhances a robot's ability to dexterously manipulate unfamiliar objects and safely interact with humans. Giving touch sensitivity to robots requires compact, robust, affordable, and efficient hardware designs, especially for high-resolution tactile sensing. We present a soft vision-based tactile sensor engineered to meet these requirements. Comparable in size to a human fingertip, Minsight uses machine learning to output high-resolution directional contact force distributions at 60 Hz. Minsight's tactile force maps enable precise sensing of fingertip contacts, which we use in this hands-on demonstration to allow a 3-DoF robot arm to physically track contact with a user's finger. While observing the colorful image captured by Minsight's internal camera, attendees can experience how its ability to detect delicate touches in all directions facilitates real-time robot interaction.
Author(s): | Iris Andrussow and Huanbo Sun and Georg Martius and Katherine J. Kuchenbecker |
Year: | 2024 |
Month: | November |
Department(s): | Autonomous Learning, Empirical Inference, Haptic Intelligence |
Research Project(s): |
Insight: a Haptic Sensor Powered by Vision and Machine Learning
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Bibtex Type: | Miscellaneous (misc) |
Paper Type: | Demonstration |
Address: | Munich, Germany |
How Published: | Hands-on demonstration presented at the Conference on Robot Learning (CoRL) |
State: | Accepted |
BibTex @misc{Andrussow24-CORLD-Minsight, title = {Demonstration: Minsight - A Soft Vision-Based Tactile Sensor for Robotic Fingertips}, author = {Andrussow, Iris and Sun, Huanbo and Martius, Georg and Kuchenbecker, Katherine J.}, howpublished = {Hands-on demonstration presented at the Conference on Robot Learning (CoRL)}, address = {Munich, Germany}, month = nov, year = {2024}, doi = {}, month_numeric = {11} } |