Labeling for a learning mobile robot

Abstract : This paper describes an approach to ground names of objects seen by a mobile robot in a real world environment. Names are given by a human teacher and axe stored within a lexicon, along with images where the corresponding objects are present. Here, the building of a high-level perceptual system is required to enable an efficient learning of the physical definition of objects. The paper briefly describes how an abstraction-based reformulation of real world data can highlight relevant information for a given concept.
Document type :
Conference papers
Complete list of metadatas
Contributor : Lip6 Publications <>
Submitted on : Thursday, August 3, 2017 - 5:18:08 PM
Last modification on : Thursday, March 21, 2019 - 1:09:53 PM


  • HAL Id : hal-01571856, version 1


Nicolas Bredèche, Jean-Daniel Zucker. Labeling for a learning mobile robot. AAAI Fall Symposium on "Anchoring Symbols to Sensor Data in Single and Multiple Robot Systems", Nov 2001, North Falmouth, Massachusetts, United States. ⟨hal-01571856⟩



Record views