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

6 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 二月

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Signal Processing
  • Hardware and Architecture
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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