A Real Application of an Autonomous Industrial Mobile Manipulator within Industrial Context
In modern industry there are still a large number of low added-value processes that can be automated or semi-automated with safe cooperation between robot and human operators. The European SHERLOCK project aims to integrate an autonomous industrial mobile manipulator (AIMM) to perform cooperative ta...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-05-01
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| Series: | Electronics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-9292/10/11/1276 |
| _version_ | 1797532469841362944 |
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| author | Jose Luis Outón Ibon Merino Iván Villaverde Aitor Ibarguren Héctor Herrero Paul Daelman Basilio Sierra |
| author_facet | Jose Luis Outón Ibon Merino Iván Villaverde Aitor Ibarguren Héctor Herrero Paul Daelman Basilio Sierra |
| author_sort | Jose Luis Outón |
| collection | DOAJ |
| description | In modern industry there are still a large number of low added-value processes that can be automated or semi-automated with safe cooperation between robot and human operators. The European SHERLOCK project aims to integrate an autonomous industrial mobile manipulator (AIMM) to perform cooperative tasks between a robot and a human. To be able to do this, AIMMs need to have a variety of advanced cognitive skills like autonomous navigation, smart perception and task management. In this paper, we report the project’s tackle in a paradigmatic industrial application combining accurate autonomous navigation with deep learning-based 3D perception for pose estimation to locate and manipulate different industrial objects in an unstructured environment. The proposed method presents a combination of different technologies fused in an AIMM that achieve the proposed objective with a success rate of 83.33% in tests carried out in a real environment. |
| first_indexed | 2024-03-10T11:00:38Z |
| format | Article |
| id | doaj.art-93684c235f3341d9a2daaa4786066175 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-10T11:00:38Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-93684c235f3341d9a2daaa47860661752023-11-21T21:34:39ZengMDPI AGElectronics2079-92922021-05-011011127610.3390/electronics10111276A Real Application of an Autonomous Industrial Mobile Manipulator within Industrial ContextJose Luis Outón0Ibon Merino1Iván Villaverde2Aitor Ibarguren3Héctor Herrero4Paul Daelman5Basilio Sierra6Tecnalia Research and Innovation, Basque Research and Technology Alliance (BRTA), Industry and Transport Division, 20009 San Sebastián, SpainTecnalia Research and Innovation, Basque Research and Technology Alliance (BRTA), Industry and Transport Division, 20009 San Sebastián, SpainTecnalia Research and Innovation, Basque Research and Technology Alliance (BRTA), Industry and Transport Division, 20009 San Sebastián, SpainTecnalia Research and Innovation, Basque Research and Technology Alliance (BRTA), Industry and Transport Division, 20009 San Sebastián, SpainTecnalia Research and Innovation, Basque Research and Technology Alliance (BRTA), Industry and Transport Division, 20009 San Sebastián, SpainTecnalia Research and Innovation, Basque Research and Technology Alliance (BRTA), Industry and Transport Division, 20009 San Sebastián, SpainRobotics and Autonomous Systems Group, University of the Basque Country UPV/EHU, 20009 San Sebastián, SpainIn modern industry there are still a large number of low added-value processes that can be automated or semi-automated with safe cooperation between robot and human operators. The European SHERLOCK project aims to integrate an autonomous industrial mobile manipulator (AIMM) to perform cooperative tasks between a robot and a human. To be able to do this, AIMMs need to have a variety of advanced cognitive skills like autonomous navigation, smart perception and task management. In this paper, we report the project’s tackle in a paradigmatic industrial application combining accurate autonomous navigation with deep learning-based 3D perception for pose estimation to locate and manipulate different industrial objects in an unstructured environment. The proposed method presents a combination of different technologies fused in an AIMM that achieve the proposed objective with a success rate of 83.33% in tests carried out in a real environment.https://www.mdpi.com/2079-9292/10/11/1276autonomous industrial mobile manipulatordeep learningroboticsperceptionsensor fusionautonomous navigation |
| spellingShingle | Jose Luis Outón Ibon Merino Iván Villaverde Aitor Ibarguren Héctor Herrero Paul Daelman Basilio Sierra A Real Application of an Autonomous Industrial Mobile Manipulator within Industrial Context Electronics autonomous industrial mobile manipulator deep learning robotics perception sensor fusion autonomous navigation |
| title | A Real Application of an Autonomous Industrial Mobile Manipulator within Industrial Context |
| title_full | A Real Application of an Autonomous Industrial Mobile Manipulator within Industrial Context |
| title_fullStr | A Real Application of an Autonomous Industrial Mobile Manipulator within Industrial Context |
| title_full_unstemmed | A Real Application of an Autonomous Industrial Mobile Manipulator within Industrial Context |
| title_short | A Real Application of an Autonomous Industrial Mobile Manipulator within Industrial Context |
| title_sort | real application of an autonomous industrial mobile manipulator within industrial context |
| topic | autonomous industrial mobile manipulator deep learning robotics perception sensor fusion autonomous navigation |
| url | https://www.mdpi.com/2079-9292/10/11/1276 |
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