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Active Visual Object Search in Unknown Environments Using Uncertain Semantics
KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.ORCID-id: 0000-0002-1396-0102
KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.ORCID-id: 0000-0002-1170-7162
2013 (engelsk)Inngår i: IEEE Transactions on robotics, ISSN 1552-3098, E-ISSN 1941-0468, Vol. 29, nr 4, s. 986-1002Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

In this paper, we study the problem of active visual search (AVS) in large, unknown, or partially known environments. We argue that by making use of uncertain semantics of the environment, a robot tasked with finding an object can devise efficient search strategies that can locate everyday objects at the scale of an entire building floor, which is previously unknown to the robot. To realize this, we present a probabilistic model of the search environment, which allows for prioritizing the search effort to those parts of the environment that are most promising for a specific object type. Further, we describe a method for reasoning about the unexplored part of the environment for goal-directed exploration with the purpose of object search. We demonstrate the validity of our approach by comparing it with two other search systems in terms of search trajectory length and time. First, we implement a greedy coverage-based search strategy that is found in previous work. Second, we let human participants search for objects as an alternative comparison for our method. Our results show that AVS strategies that exploit uncertain semantics of the environment are a very promising idea, and our method pushes the state-of-the-art forward in AVS.

sted, utgiver, år, opplag, sider
2013. Vol. 29, nr 4, s. 986-1002
Emneord [en]
Active vision, semantic mapping, visual object search
HSV kategori
Identifikatorer
URN: urn:nbn:se:kth:diva-127759DOI: 10.1109/TRO.2013.2256686ISI: 000322836600014Scopus ID: 2-s2.0-84882315603OAI: oai:DiVA.org:kth-127759DiVA, id: diva2:646027
Merknad

QC 20130906

Tilgjengelig fra: 2013-09-06 Laget: 2013-09-05 Sist oppdatert: 2017-12-06bibliografisk kontrollert

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