Map building through pseudo dense scan matching using visual sonar data |
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Authors: | Young-Ho Choi Se-Young Oh |
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Affiliation: | (1) Department of Electrical Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea |
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Abstract: | This paper presents a novel approach to the vision based grid map building and localization problem that works in a complex
indoor environment with a single forward viewing camera. Most existing visual SLAM has been limited to the feature-based method
and only a few researchers have proposed visual SLAM methods for building a grid map using a stereo vision system which has
not been popular in practical application. In this paper, we estimate the planar depth by applying a simple visual sonar ranging
technique to the single camera image and then associating sequential scans through our own pseudo dense adaptive scan matching
algorithm reducing the processing time compared to the standard point-to-point correspondence based algorithm and finally
produce a grid map. To this end, we construct a Pseudo Dense Scan (PDS) which is an odometry based temporal accumulation of
the visual sonar readings emulating omni-directional sensing in order to overcome the sparseness of the visual sonar. Moreover,
in order to obtain a much more refined map, we further correct the slight trajectory error incurred in the PDS construction
step using Sequential Quadratic Programming (SQP) which is a well-known optimization scheme. Experimental results show that
our method can obtain an accurate grid map using a single camera without the need for a high price range sensors or stereo
camera.
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Keywords: | Robust visual sonar Pseudo dense scan Adaptive scan matching Trajectory correction |
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