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Proceedings Paper

Toward a perception and sensor fusion architecture for a robotic airship
Author(s): Alberto Elfes; Jose Reginaldo H. Carvalho; Marcel Bergerman; Samuel S. Bueno
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Paper Abstract

Robotic unmanned aerial vehicles have an enormous potential as observation and data-gathering platforms for a wide variety of applications. This paper discusses components of a perception architecture being developed for AURORA (Autonomous Unmanned Remote Monitoring Robotic Airship). The AURORA project focuses on the development of the technologies required for substantially autonomous unmanned aerial vehicles, and for robotic airships in particular. We describe our approach to spatial representation, which incorporates a Markov Random Field (MRF) model used for encoding spatial inferences obtained from sensor imagery. We present a dynamic approach to target recognition that uses a cycle of hypothesis formulation, experiment planning for hypothesis validation, experiment execution, and hypothesis evaluation to confirm or reject the classification of targets into object classes. We also discuss an approach to automatic hovering and landing using visual servoing techniques and interaction matrices, and present preliminary experimental results from our work.

Paper Details

Date Published: 4 October 2001
PDF: 11 pages
Proc. SPIE 4571, Sensor Fusion and Decentralized Control in Robotic Systems IV, (4 October 2001); doi: 10.1117/12.444170
Show Author Affiliations
Alberto Elfes, Research Institute for Applied Knowledge Processing (Germany)
Jose Reginaldo H. Carvalho, Institute of Information Technology (Brazil)
Marcel Bergerman, Institute of Information Technology (Brazil)
Samuel S. Bueno, Institute of Information Technology (Brazil)

Published in SPIE Proceedings Vol. 4571:
Sensor Fusion and Decentralized Control in Robotic Systems IV
Gerard T. McKee; Paul S. Schenker, Editor(s)

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