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Journal article

Active exploration for robust object detection

Abstract:

Today, mobile robots are increasingly expected to operate in ever more complex and dynamic environments. In order to carry out many of the higher-level tasks envisioned a semantic understanding of a workspace is pivotal. Here our field has benefited significantly from successes in machine learning and vision: applications in robotics of off-the-shelf object detectors are plentiful. This paper outlines an online, any-time planning framework enabling the active exploration of such detections. O...

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Journal:
IJCAI International Joint Conference on Artificial Intelligence
Pages:
2752-2757
Publication date:
2011-01-01
DOI:
ISSN:
1045-0823
URN:
uuid:9eb877cd-8475-440e-ac51-a44aa8b9badc
Source identifiers:
417059
Local pid:
pubs:417059
Language:
English

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