Making a robotic scene representation accessible to feature and label queries

We present a neural architecture for scene representation that stores semantic information about objects in the robot's workspace. We show how this representation can be queried both through low-level features such as color and size, through feature conjunctions, as well as through symbolic lab...

Full description

Saved in:
Bibliographic Details
Main Authors: Zibner, S. K. U., Faubel, C., Schoner, G.
Format: Conference Proceeding
Language:English
Subjects:
Image color analysis
Robots
Citations: Items that cite this one
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We present a neural architecture for scene representation that stores semantic information about objects in the robot's workspace. We show how this representation can be queried both through low-level features such as color and size, through feature conjunctions, as well as through symbolic labels. This is possible by binding different feature dimensions through space and integrating these space-feature representations with an object recognition system. Queries lead to the activation of a neural representation of previously seen objects, which can then be used to drive object-oriented action. The representation is continuously linked to sensory information and autonomously updates when objects are moved or removed.
ISSN:2161-9476
DOI:10.1109/DEVLRN.2011.6037360