PixelLaser: Learning Range via Texture
نویسندگان
چکیده
The problem of finding a robot's range-to-obstacles is a fundamental one with an elegant solution: the laser range finder (LRF). This work has developed algorithms for replacing a laser with a camera for indoor applications. Our approach uses machine learning algorithms to segment the groundplane from single images flexibly, quickly, and robustly. We then transform those segmentations into laserscan-like estimates of local conditions. Current work is investigating whether off-the-shelf algorithms for mapping, localization, and navigation with LRFs work without alteration using these “pixel”-scans.
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