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Indoor map construction algorithm based on RGBD semantic segmentation

Published: 14 October 2022 Publication History

Abstract

In the field of robotics and autonomous driving, vision or laser-based map construction has always been the main direction for solving mobile vehicle's perception and localization. The stereo camera is widely used in robot map construction because it can perceive both color information and depth information. Based on the RGBD semantic segmentation network, this paper proposes a map construction algorithm based on deep semantic segmentation. By using the pixel information of deep semantic segmentation, the missing part of the 3D point cloud is filled to construct an octomap. After experiments, on the datasets, the algorithm has achieved better results than only using the depth information, and after actual deployment, the algorithm has completed the construction of real-time indoor semantic maps on the robot.

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cover image ACM Other conferences
ICCIR '22: Proceedings of the 2022 2nd International Conference on Control and Intelligent Robotics
June 2022
905 pages
ISBN:9781450397179
DOI:10.1145/3548608
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 14 October 2022

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