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Shared environment representation for a human-robot team performing information fusion

  • This paper addresses the problem of building a shared environment representation by a human-robot team. Rich environment models are required in real applications for both autonomous operation of robots and to support human decision-making. Two probabilistic models are used to describe outdoor environment features such as trees: geometric (position in the world) and visual. The visual representation is used to improve data association and to classify features. Both models are able to incorporate observations from robotic platforms and human operators. Physically, humans and robots form a heterogeneous sensor network. In our experiments, the human-robot team consists of an unmanned air vehicle, a ground vehicle, and two human operators. They are deployed for an information gathering task and perform information fusion cooperatively. All aspects of the system including the fusion algorithms are fully decentralized. Experimental results are presented in form of the acquired multi-attribute feature map, information exchange patterns demonstrating human-robot information fusion, and quantitative model evaluation. Learned lessons from deploying the system in the field are also presented. © 2007 Wiley Periodicals, Inc.

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Metadaten
Author:Tobias Kaupp, Bertrand Douillard, Fabio Ramos, Alexei Makarenko, Ben Upcroft
DOI:https://doi.org/10.1002/rob.20201
Parent Title (English):Journal of Field Robotics: Special Issue on Teamwork
Document Type:Article
Language:English
Year of publication:2007
Release Date:2023/08/11
Volume:24
Issue:11-12
Pages/Size:32
First Page:911
Last Page:942
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