Evaluation of three vision based object perception methods for a mobile robot

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

Research output: Contribution to journalArticleResearchpeer-review

9 Citations (Scopus)


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. © Springer Science+Business Media B.V. 2012.
Original languageEnglish
Pages (from-to)185-208
JournalJournal of Intelligent and Robotic Systems: Theory and Applications
Publication statusPublished - 1 Nov 2012


  • Mobile robots
  • Object recognition

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