A modified YOLOv3 detection method for vision-based water surface garbage capture robot
To tackle the water surface pollution problem, a vision-based water surface garbage capture robot has been developed in our lab. In this article, we present a modified you only look once v3-based garbage detection method, allowing real-time and high-precision object detection in dynamic aquatic envi...
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| Published in: | International journal of advanced robotic systems Vol. 17; no. 3 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
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London, England
SAGE Publications
01.05.2020
Sage Publications Ltd SAGE Publishing |
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| ISSN: | 1729-8806, 1729-8814 |
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| Abstract | To tackle the water surface pollution problem, a vision-based water surface garbage capture robot has been developed in our lab. In this article, we present a modified you only look once v3-based garbage detection method, allowing real-time and high-precision object detection in dynamic aquatic environments. More specifically, to improve the real-time detection performance, the detection scales of you only look once v3 are simplified from 3 to 2. Besides, to guarantee the accuracy of detection, the anchor boxes of our training data set are reclustered for replacing some of the original you only look once v3 prior anchor boxes that are not appropriate to our data set. By virtue of the proposed detection method, the capture robot has the capability of cleaning floating garbage in the field. Experimental results demonstrate that both detection speed and accuracy of the modified you only look once v3 are better than those of other object detection algorithms. The obtained results provide valuable insight into the high-speed detection and grasping of dynamic objects in complex aquatic environments autonomously and intelligently. |
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| AbstractList | To tackle the water surface pollution problem, a vision-based water surface garbage capture robot has been developed in our lab. In this article, we present a modified you only look once v3-based garbage detection method, allowing real-time and high-precision object detection in dynamic aquatic environments. More specifically, to improve the real-time detection performance, the detection scales of you only look once v3 are simplified from 3 to 2. Besides, to guarantee the accuracy of detection, the anchor boxes of our training data set are reclustered for replacing some of the original you only look once v3 prior anchor boxes that are not appropriate to our data set. By virtue of the proposed detection method, the capture robot has the capability of cleaning floating garbage in the field. Experimental results demonstrate that both detection speed and accuracy of the modified you only look once v3 are better than those of other object detection algorithms. The obtained results provide valuable insight into the high-speed detection and grasping of dynamic objects in complex aquatic environments autonomously and intelligently. |
| Author | Tian, Manjun Yu, Junzhi Kong, Shihan Wu, Licheng Li, Xiali |
| Author_xml | – sequence: 1 givenname: Xiali orcidid: 0000-0001-7950-6204 surname: Li fullname: Li, Xiali – sequence: 2 givenname: Manjun surname: Tian fullname: Tian, Manjun – sequence: 3 givenname: Shihan surname: Kong fullname: Kong, Shihan – sequence: 4 givenname: Licheng orcidid: 0000-0001-5739-634X surname: Wu fullname: Wu, Licheng – sequence: 5 givenname: Junzhi orcidid: 0000-0002-6347-572X surname: Yu fullname: Yu, Junzhi email: junzhi.yu@ia.ac.cn |
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| Keywords | garbage capture robot detection modified YOLOv3 aquatic environment Object detection |
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| SubjectTerms | Algorithms Anchors Aquatic environment Boxes Computer vision Datasets Garbage Grasping (robotics) Object recognition Real time Robots Water pollution |
| Title | A modified YOLOv3 detection method for vision-based water surface garbage capture robot |
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