Multi-step Pick-and-Place Tasks Using Object-centric Dense Correspondences

Chun Yu Chai, Keng Fu Hsu, Shiao-Li Tsao

研究成果: Conference contribution同行評審

1 引文 斯高帕斯(Scopus)

摘要

This paper presents an object-centric method for efficiently performing two types of challenging pick-and-place tasks, namely sequential pick and place and object sorting. We propose multiclass dense object nets (MCDONs) for learning object-centric dense descriptors that maintain not only intra-class variations but also inter-class separation. Intra-class consistency is also inherently learned and is useful for our pick-and-place tasks. All the tasks only require a single demonstration from users, which can then be generalized to all class instances. A dataset containing eight classes and a total of 52 objects was provided in this study. We obtained a task success rate of 93.33% on a five-block stacking task and 97.41% on a three-class object sorting task.

原文English
主出版物標題2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
發行者Institute of Electrical and Electronics Engineers Inc.
頁面4004-4011
頁數8
ISBN(電子)9781728140049
DOIs
出版狀態Published - 十一月 2019
事件2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019 - Macau, China
持續時間: 3 十一月 20198 十一月 2019

出版系列

名字IEEE International Conference on Intelligent Robots and Systems
ISSN(列印)2153-0858
ISSN(電子)2153-0866

Conference

Conference2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
國家China
城市Macau
期間3/11/198/11/19

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