Visual-Guided Robot Arm Using Multi-Task Faster R-CNN

Phong Phu Le, Van Thanh Nguyen, Shu Mei Guo, Ching Ting Tu, Jenn Jier James Lien

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

Abstract

The limitation of current visual recognition methods is a big obstacle for the application of automated robot arm systems into industrial projects, which require high precision and speed. In this work, we present a Faster RCNN based multi-task network, a deep neural network model, that is able to simultaneously perform three tasks including object detection, category classification and object angle estimation. Afterward, the outputs of all three tasks are utilized to decide a picking point and a rotated gripper angle for the pick-and-place robot arm system. The test results show that our network achieves a mean average precision of 86.6% at IoU (Intersection over Union) of 0.7, and a mean accuracy of 83.5% for the final prediction including object localization and angle estimation. In addition, the proposed multi-task network takes approximately 0.072 seconds to process an image, which is acceptable for pick-and-place robot arms.

Original languageEnglish
Title of host publicationProceedings - 2019 International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728146669
DOIs
Publication statusPublished - 2019 Nov
Event24th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019 - Kaohsiung, Taiwan
Duration: 2019 Nov 212019 Nov 23

Publication series

NameProceedings - 2019 International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019

Conference

Conference24th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019
CountryTaiwan
CityKaohsiung
Period19-11-2119-11-23

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction

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  • Cite this

    Le, P. P., Nguyen, V. T., Guo, S. M., Tu, C. T., & Lien, J. J. J. (2019). Visual-Guided Robot Arm Using Multi-Task Faster R-CNN. In Proceedings - 2019 International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019 [8959938] (Proceedings - 2019 International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TAAI48200.2019.8959938