Learning context-aware mobile robot navigation in home environmentsShow others and affiliations
2014 (English)In: IISA 2014: The 5th International Conference on Information, Intelligence, Systems and Applications, New York: Institute of Electrical and Electronics Engineers (IEEE), 2014, p. 57-62, article id 6878733Conference paper, Published paper (Refereed)
Abstract [en]
We present an approach to make planning adaptive in order to enable context-aware mobile robot navigation. We integrate a model-based planner with a distributed learning system based on reservoir computing, to yield personalized planning and resource allocations that account for user preferences and environmental changes. We demonstrate our approach in a real robot ecology, and show that the learning system can effectively exploit historical data about navigation performance to modify the models in the planner, without any prior information oncerning the phenomenon being modeled. The plans produced by the adapted CL fail more rarely than the ones generated by a non-adaptive planner. The distributed learning system handles the new learning task autonomously, and is able to automatically identify the sensorial information most relevant for the task, thus reducing the communication and computational overhead of the predictive task.
Place, publisher, year, edition, pages
New York: Institute of Electrical and Electronics Engineers (IEEE), 2014. p. 57-62, article id 6878733
National Category
Robotics and automation Computer Sciences
Research subject
Computer Science; Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-55288DOI: 10.1109/IISA.2014.6878733ISI: 000345861900012Scopus ID: 2-s2.0-84906748619OAI: oai:DiVA.org:oru-55288DiVA, id: diva2:1071066
Conference
5th International Conference on Information, Intelligence, Systems and Applications (IISA 2014), Chania, Crete, Greece, July 7-9, 2014
Projects
EU FP7 RUBICON
Funder
EU, FP7, Seventh Framework Programme, 2699142017-02-032017-02-032025-02-05Bibliographically approved