Object Recognition Using Flexible Tactile Sensor

• Shoshi, Tokuno

• Yuichiro, Tanaka

• Takumi, Kawasetsu

• Koh, Hosoda

• Hakaru, Tamukoh

抄録

We propose an object recognition system based on tactile information obtained from a tactile sensor. Our tactile sensor is made of flexible materials and composed of three parts: silicon rubber, liquid metal, and a coil printed on a circuit board. The sensor is mounted on a robot hand to acquire the tactile information of grasped objects. The tactile information for object classification is learned by an echo state network (ESN). The tactile time series data acquired by the tactile sensor are fed into the ESN for training and classification. To determine whether the system can classify two objects with different hardness levels and two objects with similar colors which cannot be classified by an image recognition system, we conducted two experiments. The classification accuracy of two objects with different hardness levels was 90%, and that of two objects with similar colors was 100%.

We propose an object recognition system based on tactile information obtained from a tactile sensor. Our tactile sensor is made of flexible materials and composed of three parts: silicon rubber, liquid metal, and a coil printed on a circuit board. The sensor is mounted on a robot hand to acquire the tactile information of grasped objects. The tactile information for object classification is learned by an echo state network (ESN). The tactile time series data acquired by the tactile sensor are fed into the ESN for training and classification. To determine whether the system can classify two objects with different hardness levels and two objects with similar colors which cannot be classified by an image recognition system, we conducted two experiments. The classification accuracy of two objects with different hardness levels was 90%, and that of two objects with similar colors was 100%.

収録刊行物

• Proceedings of Asia Pacific Conference on Robot IoT System Development and Platform

  Proceedings of Asia Pacific Conference on Robot IoT System Development and Platform 2020 81-82, 2021-03-15

詳細情報

• CRID: 1050292572093451520
• NII論文ID: 170000184470
• Web Site: http://id.nii.ac.jp/1001/00210235/
• 本文言語コード: en
• 資料種別: conference paper
• データソース種別:
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