Minsight: A Fingertip-Sized Vision-Based Tactile Sensor for Robotic Manipulation

被引:34
作者
Andrussow, Iris [1 ,2 ]
Sun, Huanbo [2 ]
Kuchenbecker, Katherine J. J. [1 ]
Martius, Georg [2 ]
机构
[1] Max Planck Inst Intelligent Syst, Hapt Intelligence Dept, Heisenbergstr 3, D-70569 Stuttgart, Germany
[2] Max Planck Inst Intelligent Syst, Autonomous Learning Grp, Max Planck Ring 4, D-72076 Tubingen, Germany
关键词
machine learning; robot fingertips; soft robotics; tactile sensing for manipulation; vision-based haptics; FORCE; RESOLUTION; SKIN; DESIGN;
D O I
10.1002/aisy.202300042
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Intelligent interaction with the physical world requires perceptual abilities beyond vision and hearing; vibrant tactile sensing is essential for autonomous robots to dexterously manipulate unfamiliar objects or safely contact humans. Therefore, robotic manipulators need high-resolution touch sensors that are compact, robust, inexpensive, and efficient. The soft vision-based haptic sensor presented herein is a miniaturized and optimized version of the previously published sensor Insight. Minsight has the size and shape of a human fingertip and uses machine learning methods to output high-resolution maps of 3D contact force vectors at 60 Hz. Experiments confirm its excellent sensing performance, with a mean absolute force error of 0.07 N and contact location error of 0.6 mm across its surface area. Minsight's utility is shown in two robotic tasks on a 3-DoF manipulator. First, closed-loop force control enables the robot to track the movements of a human finger based only on tactile data. Second, the informative value of the sensor output is shown by detecting whether a hard lump is embedded within a soft elastomer with an accuracy of 98%. These findings indicate that Minsight can give robots the detailed fingertip touch sensing needed for dexterous manipulation and physical human-robot interaction.
引用
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页数:10
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