Journal article
The STRANDS project: Long-term autonomy in everyday environments
- Abstract:
- Thanks to the efforts of the robotics and autonomous systems community, the myriad applications and capacities of robots are ever increasing. There is increasing demand from end users for autonomous service robots that can operate in real environments for extended periods. In the Spatiotemporal Representations and Activities for Cognitive Control in Long-Term Scenarios (STRANDS) project (http://strandsproject.eu), we are tackling this demand head-on by integrating state-of-the-art artificial intelligence and robotics research into mobile service robots and deploying these systems for long-term installations in security and care environments. Our robots have been operational for a combined duration of 104 days over four deployments, autonomously performing end-user-defined tasks and traversing 116 km in the process. In this article, we describe the approach we used to enable long-term autonomous operation in everyday environments and how our robots are able to use their long run times to improve their own performance.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Accepted manuscript, pdf, 3.2MB, Terms of use)
-
- Publisher copy:
- 10.1109/MRA.2016.2636359
Authors
+ European Union
More from this funder
- Grant:
- Seventh Framework Program (FP7/2007-2013) under grant agreement No. 600623, STRANDS
- Publisher:
- IEEE
- Journal:
- IEEE Robotics and Automation Magazine More from this journal
- Volume:
- 24
- Issue:
- 3
- Pages:
- 146-156
- Publication date:
- 2017-06-14
- Acceptance date:
- 2017-01-15
- DOI:
- ISSN:
-
1070-9932
- Pubs id:
-
pubs:821108
- UUID:
-
uuid:74bd9aa7-0cab-43a9-be3b-4f8762f6f4f1
- Local pid:
-
pubs:821108
- Source identifiers:
-
821108
- Deposit date:
-
2018-01-24
Terms of use
- Copyright holder:
- IEEE
- Copyright date:
- 2017
- Notes:
- Copyright © 2017 IEEE. This is the accepted manuscript version of the article. The final version is available online from IEEE at: https://doi.org/10.1109/MRA.2016.2636359
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