The STRANDS project: long-term autonomy in everyday environments

Hawes, Nick and Burbridge, Christopher and Jovan, Ferdian and Kunze, Lars and Lacerda, Bruno and Mudrova, Lenka and Young, Jay and Wyatt, Jeremy and Hebesberger, Denise and Kortner, Tobias and Ambrus, Rares and Bore, Nils and Folkesson, John and Jensfelt, Patric and Beyer, Lucas and Hermans, Alexander and Leibe, Bastian and Aldoma, Aitor and Faulhammer, Thomas and Zillich, Michael and Vincze, Markus and Chinellato, Eris and Al-Omari, Muhannad and Duckworth, Paul and Gatsoulis, Yiannis and Hogg, David C. and Cohn, Anthony G. and Dondrup, Christian and Pulido Fentanes, Jaime and Krajnik, Tomas and Santos, Joao M. and Duckett, Tom and Hanheide, Marc (2017) The STRANDS project: long-term autonomy in everyday environments. IEEE Robotics & Automation Magazine, 24 (3). pp. 146-156. ISSN 1070-9932

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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 (, 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.

Item Type: Article
Research Areas: A. > School of Science and Technology
Item ID: 23829
Notes on copyright: © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
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Depositing User: Eris Chinellato
Date Deposited: 08 Mar 2018 15:42
Last Modified: 07 Nov 2018 22:58

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