A Real Application of an Autonomous Industrial Mobile Manipulator within Industrial Context

Thumbnail Image
Files
electronics-10-01276.pdf (17.6 MB)
Identifiers
URI: http://hdl.handle.net/11556/1145
ESSN: 2079-9292
DOI: 10.3390/electronics10111276
Publication date
2021-05-27
Authors
Advisors
Journal Title
Journal ISSN
Volume Title
Publisher
Multidisciplinary Digital Publishing Institute (MDPI)
Citations
Google Scholar
Export
Research Projects
Organizational Units
Journal Issue
Abstract
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.
Description
Keywords
Autonomous industrial mobile manipulator , Deep learning , Robotics , Perception , Sensor fusion , Autonomous navigation , Computer vision , Skills , State machine
Type
journal article
Citation
Outón, Jose Luis, Ibon Merino, Iván Villaverde, Aitor Ibarguren, Héctor Herrero, Paul Daelman, and Basilio Sierra. “A Real Application of an Autonomous Industrial Mobile Manipulator Within Industrial Context.” Electronics 10, no. 11 (May 27, 2021): 1276. doi:10.3390/electronics10111276.