Stereo vision-based object recognition and manipulation by regions with convolutional neural network

Yi Chun Du, Muslikhin Muslikhin, Tsung Han Hsieh, Ming Shyan Wang

研究成果: Article同行評審

30 引文 斯高帕斯(Scopus)

摘要

This paper develops a hybrid algorithm of adaptive network-based fuzzy inference system (ANFIS) and regions with convolutional neural network (R-CNN) for stereo vision-based object recognition and manipulation. The stereo camera at an eye-to-hand configuration firstly captures the image of the target object. Then, the shape, features, and centroid of the object are estimated. Similar pixels are segmented by the image segmentation method, and similar regions are merged through selective search. The eye-to-hand calibration is based on ANFIS to reduce computing burden. A six-degree-of-freedom (6-DOF) robot arm with a gripper will conduct experiments to demonstrate the effectiveness of the proposed system.

原文English
文章編號210
期刊Electronics (Switzerland)
9
發行號2
DOIs
出版狀態Published - 2020 2月

All Science Journal Classification (ASJC) codes

  • 控制與系統工程
  • 訊號處理
  • 硬體和架構
  • 電腦網路與通信
  • 電氣與電子工程

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