Towards Estimating the Stiffness of Soft Fruits using a Piezoresistive Tactile Sensor and Neural Network Schemes

Frank Efe Erukainure, Victor Parque, Mohsen A. Hassan, Ahmed M.R. Fathelbab

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Measuring the ripeness of fruits is one of the key challenges to enable optimal and just-in-time strategies across the fruit supply chain. In this paper, we study the performance of a tactile sensor to estimate the ground truth of the stiffness of fruits, with kiwifruit as a case study. Our sensor configuration is based on a three-beam cantilever arrangement with piezoresistive elements, enabling the stable acquisition of sensor readings over independent trials. Our estimation scheme is based on the com-pact feed-forward neural networks, allowing us to find effective nonlinear relationships between instantaneous sensor readings and the ground truth of stiffness of fruits. Our experiments using several kiwifruit specimens show the competitive performance frontiers of stiffness approximation using 25 compact feed-forward neural networks, converging to MSE loss at 10-5 across training-validation-testing in most of the cases, and the utmost predictive performance of a pyramidal class of feed-forward architectures. Our results pinpoint the potential to realize robust fruit ripeness measurement with intelligent tactile sensors.

本文言語English
ホスト出版物のタイトル2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2022
出版社Institute of Electrical and Electronics Engineers Inc.
ページ290-295
ページ数6
ISBN(電子版)9781665413084
DOI
出版ステータスPublished - 2022
イベント2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2022 - Sapporo, Japan
継続期間: 2022 7月 112022 7月 15

出版物シリーズ

名前IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM
2022-July

Conference

Conference2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2022
国/地域Japan
CitySapporo
Period22/7/1122/7/15

ASJC Scopus subject areas

  • 電子工学および電気工学
  • 制御およびシステム工学
  • コンピュータ サイエンスの応用
  • ソフトウェア

フィンガープリント

「Towards Estimating the Stiffness of Soft Fruits using a Piezoresistive Tactile Sensor and Neural Network Schemes」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル