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Bearing-Only SLAM with Indistinguishable Landmarks

Huang, Henry, Maire, Frederic D., & Keeratipranon, Narongdech (2007) Bearing-Only SLAM with Indistinguishable Landmarks. In The 2007 Australasian Conference on Robotics and Automation (ACRA 2007), 10-12, Dec, 2007, Brisbane, Australia.

Abstract

To navigate successfully, a mobile robot must be able to estimate the spatial relationships of the objects of interest in its environment. The main advantage of a bearing-only SLAM system is that it requires only a cheap vision sensor for navigation. In this paper, we present a bearing-only SLAM method for a 2D environment with visually indistinguishable landmarks (Unknown Data Association). When the frame rate of the vision sensor is high, it is easy to track the landmark correspondences. When the frame rate is low, we estimate the landmark positions by computing the most likely hypothesis based on bearing measurements. A bearing-only SLAM system that employs this method does not require any other sensors such as range sensors or wheel encoders. Due to its low cost, this system is ideally suited for domestic robots such as autonomous lawnmowers and vacuum cleaners.

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ID Code: 12526
Item Type: Conference Paper
Additional Information: The contents of this conference can be freely accessed online via the conference’s web page (see hypertext link).
Additional URLs:
Keywords: SLAM, Indistinguishable Landmarks, Unknown Data Association
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Adaptive Agents and Intelligent Robotics (080101)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2007 (please consult author)
Deposited On: 19 Feb 2008
Last Modified: 29 Feb 2012 23:35

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