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Robotics 2017, 6(2), 9; doi:10.3390/robotics6020009

Visual Place Recognition for Autonomous Mobile Robots

Computer Engineering Group, Faculty of Technology, Bielefeld University, Bielefeld D-33615, Germany
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Author to whom correspondence should be addressed.
Academic Editor: Huosheng Hu
Received: 14 March 2017 / Revised: 10 April 2017 / Accepted: 12 April 2017 / Published: 17 April 2017

Abstract

Place recognition is an essential component of autonomous mobile robot navigation. It is used for loop-closure detection to maintain consistent maps, or to localize the robot along a route, or in kidnapped-robot situations. Camera sensors provide rich visual information for this task. We compare different approaches for visual place recognition: holistic methods (visual compass and warping), signature-based methods (using Fourier coefficients or feature descriptors (able for binary-appearance loop-closure evaluation, ABLE)), and feature-based methods (fast appearance-based mapping, FabMap). As new contributions we investigate whether warping, a successful visual homing method, is suitable for place recognition. In addition, we extend the well-known visual compass to use multiple scale planes, a concept also employed by warping. To achieve tolerance against changing illumination conditions, we examine the NSAD distance measure (normalized sum of absolute differences) on edge-filtered images. To reduce the impact of illumination changes on the distance values, we suggest to compute ratios of image distances to normalize these values to a common range. We test all methods on multiple indoor databases, as well as a small outdoor database, using images with constant or changing illumination conditions. ROC analysis (receiver-operator characteristics) and the metric distance between best-matching image pairs are used as evaluation measures. Most methods perform well under constant illumination conditions, but fail under changing illumination. The visual compass using the NSAD measure on edge-filtered images with multiple scale planes, while being slower than signature methods, performs best in the latter case. View Full-Text
Keywords: visual place recognition; holistic image processing; visual compass; robot localization visual place recognition; holistic image processing; visual compass; robot localization
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Horst, M.; Möller, R. Visual Place Recognition for Autonomous Mobile Robots. Robotics 2017, 6, 9.

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