This paper proposes a probabilistic object-object relation based approach for an active object search. An important role of mobile robots will be to perform object-related tasks and active object search strategies deal with the non-trivial task of finding an object in unstructured and dynamically changing environments. This work builds further upon an existing approach exploiting probabilistic object-room relations for selecting the room in which an object is expected to be. Learnt object-object relations allow to search for objects inside a room via a chain of intermediate objects. Simulations have been performed to investigate the effect of the camera quality on path length and failure rate. Furthermore, a comparison is made with a benchmark algorithm based the same prior knowledge but without using a chain of intermediate objects. An experiment shows the potential of the proposed approach on the AMIGO robot. © 2014 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Elfring, J., Jansen, S., Van De Molengraft, R., & Steinbuch, M. (2014). Active object search exploiting probabilistic object-object relations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8371 LNAI, pp. 13–24). Springer Verlag. https://doi.org/10.1007/978-3-662-44468-9_2
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