Embedded-based object matching and robot arm control

Minh Tri Le, Chih Hung G. Li, Shu Mei Guo, Jenn Jier James Lien

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

Abstract

We present an embedded-based robot arm grasp detection system. This system has two subsystems: an embedded vision subsystem and an embedded robot arm control subsystem. In the former, a template matching algorithm is processed into an Nvidia Jetson TX2 developer kit to detect objects. And, then, control a robot arm to grasp and place. Although embedded systems have some preferred benefits, such as: cost, weight, size and power consumption; the slow processing speed is a significant drawback. To deal with this problem, we propose methods to reduce the number of calculations on the measurement of similarity. After testing on 40 templates with 200 test images, the result shows that the average of execution time is up to 10x faster than the original. The average execution time on middle size templates, (100 \sim 200) \times (100 \sim 200) pixels, obtains 0.176sec. In addition, the angle of objects is determined with a small angle interval: 1 degree.

Original languageEnglish
Title of host publication2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019
PublisherIEEE Computer Society
Pages1296-1301
Number of pages6
ISBN (Electronic)9781728103556
DOIs
Publication statusPublished - 2019 Aug
Event15th IEEE International Conference on Automation Science and Engineering, CASE 2019 - Vancouver, Canada
Duration: 2019 Aug 222019 Aug 26

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2019-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference15th IEEE International Conference on Automation Science and Engineering, CASE 2019
CountryCanada
CityVancouver
Period19-08-2219-08-26

Fingerprint

Robots
Template matching
Embedded systems
Electric power utilization
Pixels
Testing
Processing
Costs

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Le, M. T., Li, C. H. G., Guo, S. M., & Lien, J. J. J. (2019). Embedded-based object matching and robot arm control. In 2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019 (pp. 1296-1301). [8843182] (IEEE International Conference on Automation Science and Engineering; Vol. 2019-August). IEEE Computer Society. https://doi.org/10.1109/COASE.2019.8843182
Le, Minh Tri ; Li, Chih Hung G. ; Guo, Shu Mei ; Lien, Jenn Jier James. / Embedded-based object matching and robot arm control. 2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019. IEEE Computer Society, 2019. pp. 1296-1301 (IEEE International Conference on Automation Science and Engineering).
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Le, MT, Li, CHG, Guo, SM & Lien, JJJ 2019, Embedded-based object matching and robot arm control. in 2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019., 8843182, IEEE International Conference on Automation Science and Engineering, vol. 2019-August, IEEE Computer Society, pp. 1296-1301, 15th IEEE International Conference on Automation Science and Engineering, CASE 2019, Vancouver, Canada, 19-08-22. https://doi.org/10.1109/COASE.2019.8843182

Embedded-based object matching and robot arm control. / Le, Minh Tri; Li, Chih Hung G.; Guo, Shu Mei; Lien, Jenn Jier James.

2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019. IEEE Computer Society, 2019. p. 1296-1301 8843182 (IEEE International Conference on Automation Science and Engineering; Vol. 2019-August).

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

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Le MT, Li CHG, Guo SM, Lien JJJ. Embedded-based object matching and robot arm control. In 2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019. IEEE Computer Society. 2019. p. 1296-1301. 8843182. (IEEE International Conference on Automation Science and Engineering). https://doi.org/10.1109/COASE.2019.8843182