Robotics: Science and Systems XIX 2023
DOI: 10.15607/rss.2023.xix.070
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InstaLoc: One-shot Global Lidar Localisation in Indoor Environments through Instance Learning

Lintong Zhang,
Sundara Digumarti,
Georgi Tinchev
et al.

Abstract: Localization for autonomous robots in prior maps is crucial for their functionality. This paper offers a solution to this problem for indoor environments called InstaLoc, which operates on an individual lidar scan to localize it within a prior map. We draw on inspiration from how humans navigate and position themselves by recognizing the layout of distinctive objects and structures. Mimicking the human approach, InstaLoc identifies and matches object instances in the scene with those from a prior map. As far a… Show more

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