Evaluation of Three Vision Based Object Perception Methods for a Mobile Robot

  • Authors:

  • Arnau Ramisa;David Aldavert;Shrihari Vasudevan;Ricardo Toledo;Ramon Lopez De Mantaras

  • Affiliations:

  • IRI UPC-CSIC, Barcelona, Spain 08028;Computer Vision Center, Dept. Ciències de la Computació, Universitat Autònoma de Barcelona, Bellaterra, Spain 08193;Australian Center for Field Robotics, The University of Sydney, Sydney, Australia NSW 2006;Computer Vision Center, Dept. Ciències de la Computació, Universitat Autònoma de Barcelona, Bellaterra, Spain 08193;IIIA-CSIC, Bellaterra, Spain 08193

  • Venue:
  • Journal of Intelligent and Robotic Systems
  • Year:
  • 2012

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Abstract

This paper addresses visual object perception applied to mobile robotics. Being able to perceive household objects in unstructured environments is a key capability in order to make robots suitable to perform complex tasks in home environments. However, finding a solution for this task is daunting: it requires the ability to handle the variability in image formation in a moving camera with tight time constraints. The paper brings to attention some of the issues with applying three state of the art object recognition and detection methods in a mobile robotics scenario, and proposes methods to deal with windowing/segmentation. Thus, this work aims at evaluating the state-of-the-art in object perception in an attempt to develop a lightweight solution for mobile robotics use/research in typical indoor settings.