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ICRA
2007
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Mini-SLAM: Minimalistic Visual SLAM in Large-Scale Environments Based on a New Interpretation of Image Similarity

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Mini-SLAM: Minimalistic Visual SLAM in Large-Scale Environments Based on a New Interpretation of Image Similarity
— This paper presents a vision-based approach to SLAM in large-scale environments with minimal sensing and computational requirements. The approach is based on a graphical representation of robot poses and links between the poses. Links between the robot poses are established based on odomety and image similarity, then a relaxation algorithm is used to generate a globally consistent map. To estimate the covariance matrix for links obtained from the vision sensor, a novel method is introduced based on the relative similarity of neighbouring images, without requiring distances to image features or multiple view geometry. Indoor and outdoor experiments demonstrate that the approach scales well to large-scale environments, producing topologically correct and geometrically accurate maps at minimal computational cost. Mini-SLAM was found to produce consistent maps in an unstructured, large-scale environment (the total path length
Henrik Andreasson, Tom Duckett, Achim J. Lilientha
Added 03 Jun 2010
Updated 03 Jun 2010
Type Conference
Year 2007
Where ICRA
Authors Henrik Andreasson, Tom Duckett, Achim J. Lilienthal
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