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Human-aware planning for robots embedded in ambient ecologies
Örebro University, School of Science and Technology. (Centre for Applied Autonomous Sensor Systems ( AASS ))
Örebro University, School of Science and Technology. (Centre for Applied Autonomous Sensor Systems ( AASS ))ORCID iD: 0000-0002-0458-2146
Örebro University, School of Science and Technology. (Centre for Applied Autonomous Sensor Systems ( AASS ))ORCID iD: 0000-0001-8229-1363
2012 (English)In: Pervasive and Mobile Computing, ISSN 1574-1192, E-ISSN 1873-1589, Vol. 8, no 4, p. 542-561Article in journal (Refereed) Published
Abstract [en]

We address the issue of human-robot cohabitation in smart environments. In particular, the presence of humans in a robot's work space has a profound influence on how the latter should plan its actions. We propose the use of Human-Aware Planning, an approach in which the robot exploits the capabilities of a sensor-rich environment to obtain information about the (current and future) activities of the people in the environment, and plans its tasks accordingly.

Here, we formally describe the planning problem behind our approach, we analyze its complexity and we detail the algorithm of our planner. We then show two application scenarios that could benefit from the techniques described. The first scenario illustrates the applicability of human-aware planning in a domestic setting, while the second one illustrates its use for a robotic helper in a hospital. Finally, we present a five hour-long test run in a smart home equipped with real sensors, where a cleaning robot has been deployed and where a human subject is acting. This test run in a real setting is meant to demonstrate the feasibility of our approach to human-robot interaction.

Place, publisher, year, edition, pages
Elsevier, 2012. Vol. 8, no 4, p. 542-561
Keywords [en]
Human-aware planning, Planning under uncertainty, Human-robot interaction, Planning in intelligent environments
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-22785DOI: 10.1016/j.pmcj.2011.11.004ISI: 000306646200005Scopus ID: 2-s2.0-84864287340OAI: oai:DiVA.org:oru-22785DiVA, id: diva2:525891
Funder
Knowledge Foundation
Note

Funding Agency;

CUGS (Swedish national computer science graduate school) 

Available from: 2012-05-09 Created: 2012-05-09 Last updated: 2018-01-12Bibliographically approved

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Cirillo, MarcelloKarlsson, LarsSaffiotti, Alessandro

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