Grasping Method in a Complex Environment using Convolutional Neural Network Based on Modified Average Filter

Da Wit Kim, Hyun Jun Jo, Jae-Bok Song

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Along with the development of deep learning, efforts are being made to grasping with the robot using only the camera. Above all, a lot of research is being done for grasping in an environment where various objects are mixed. To perform grasping in complex environments, it is necessary to train the grasping algorithm with vast amounts of data to ensure its robustness. However, collecting grasping data takes a lot of time and effort. In this paper, we proposed the depth tile that simply describes a complex situation by processing a depth image. Through this, the grasping algorithm can use a light artificial neural network, and training data can be generated automatically without grasping in real-world or simulation to minimize learning data collection costs. Artificial neural network trained through the depth tile can perform grasping with high success rate by estimating the grasping angle, which is less likely to interfere with obstacles. In this paper, the proposed grasping method, through experiments to empty randomly placed objects, is proved to be robust in complex environments.

Original languageEnglish
Title of host publication2019 16th International Conference on Ubiquitous Robots, UR 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages113-117
Number of pages5
ISBN (Electronic)9781728132327
DOIs
Publication statusPublished - 2019 Jun 1
Event16th International Conference on Ubiquitous Robots, UR 2019 - Jeju, Korea, Republic of
Duration: 2019 Jun 242019 Jun 27

Publication series

Name2019 16th International Conference on Ubiquitous Robots, UR 2019

Conference

Conference16th International Conference on Ubiquitous Robots, UR 2019
CountryKorea, Republic of
CityJeju
Period19/6/2419/6/27

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Mechanical Engineering
  • Control and Optimization

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  • Cite this

    Kim, D. W., Jo, H. J., & Song, J-B. (2019). Grasping Method in a Complex Environment using Convolutional Neural Network Based on Modified Average Filter. In 2019 16th International Conference on Ubiquitous Robots, UR 2019 (pp. 113-117). [8768779] (2019 16th International Conference on Ubiquitous Robots, UR 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/URAI.2019.8768779