Cited By
View all- Escobar-Naranjo JCaiza GAyala PJordan EGarcia CGarcia M(2023)Autonomous Navigation of Robots: Optimization with DQNApplied Sciences10.3390/app1312720213:12(7202)Online publication date: 16-Jun-2023
A Visual Learning based Robotic Grasping System
Authors: 
Weijun Guan, Yulan GuoAuthors Info & Claims
Weijun Guan, Yulan GuoAuthors Info & ClaimsPages 22 - 28
Abstract
Deep learning has promoted the development of many areas in computer vision and robotics. However, most of the researches focus on an individual task. In this paper, we design a multi-task robot system based on ROS platform and YOLO network to complete the object detection, positioning, and grasping tasks. In terms of hardware, a heterogeneous computing platform is established to achieve high computing power while reducing energy consumption. In terms of software, an algorithm framework is designed for the multi-task robot system according to the characters the heterogeneous computing platform. Experimental results on real data show that the proposed robot system achieves promising object detection, positioning and grasping performance.
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Index Terms
- A Visual Learning based Robotic Grasping System
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Published In
October 2022
164 pages
ISBN:9781450396943
DOI:10.1145/3571560
Copyright © 2022 ACM.
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Association for Computing Machinery
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Publication History
Published: 12 January 2023
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ICAAI 2022
ICAAI 2022: 2022 The 6th International Conference on Advances in Artificial Intelligence
October 21 - 23, 2022
Birmingham, United Kingdom
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Cited By
View all- Escobar-Naranjo JCaiza GAyala PJordan EGarcia CGarcia M(2023)Autonomous Navigation of Robots: Optimization with DQNApplied Sciences10.3390/app1312720213:12(7202)Online publication date: 16-Jun-2023
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