NDLI: Fast frontier detection in indoor environment for monocular SLAM

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Fast frontier detection in indoor environment for monocular SLAM

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Fast frontier detection in indoor environment for monocular SLAM

Content Provider	ACM Digital Library
Author	Krishna, K Madhava Kumar, Swagat Upadhyay, Sarthak
Abstract	Frontier detection is a critical component in autonomous exploration, wherein the robot decides the next best location to move in order to continue its mapping process. The existing frontier detection methods require dense reconstruction which is difficult to attain in a poorly textured indoor environment using a monocular camera. In this effort, we present an alternate method of detecting frontiers during the course of robot motion that circumvents the requirement of dense mapping. Based on the observation that frontiers typically occur around areas with sudden change in texture (zero-crossings), we propose a novel linear chain Conditional Random Field(CRF) formulation that is able to detect the presence or absence of frontier regions around such areas. We use cues like spread of 3D points and scene change around these areas as an observation to CRF. We demonstrate that this method gives us more relevant frontiers compared to other monocular camera based methods in the literature. Finally, we present results in an indoor environment, wherein frontiers are reliably detected around walls leading to new corridors, doors leading to new rooms or corridors and tables and other objects that open up to a new space in rooms.
Starting Page	1
Ending Page	8
Page Count	8
File Format	PDF
ISBN	9781450347532
DOI	10.1145/3009977.3010063
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-12-18
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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