Fingertip Contact Detection for a Multi-fingered Under-actuated Robotic Hand using Density-based Clustering Method
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- DOAN Ha Thang Long
- Kyushu University
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- TAHARA Kenji
- Kyushu University
書誌事項
- タイトル別名
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- Robotic Hand using Density-based Clustering Method
説明
<p>Detecting the contact of Multi-fingered robotic hand’s fingertip and an object plays an important role in grasping the object stably. However, there remained considerable difficulties due to non-ideal external factors, in which for an under-actuated finger with force sensor located at the link far from the fingertip, each contact position cannot be determined using only the kinematic model and tactile information. In this paper, the Density-based clustering method to the force sensor and position encoder data is introduced to realize real-time contact detection. In our approach, data of the finger’s joint sensor during operation when not in contact with object is collected and analyzed using Density-based clustering algorithm. Learned information and collected data are then used to perform real-time contact detection.</p>
収録刊行物
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- ロボティクス・メカトロニクス講演会講演概要集
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ロボティクス・メカトロニクス講演会講演概要集 2022 (0), 2A1-N01-, 2022
一般社団法人 日本機械学会
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詳細情報 詳細情報について
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- CRID
- 1390576037461162752
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- ISSN
- 24243124
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- Crossref
- OpenAIRE
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- 抄録ライセンスフラグ
- 使用不可