Improving google's cartographer 3D mapping by continuous-time slam

34Citations
Citations of this article
135Readers
Mendeley users who have this article in their library.

Abstract

This paper shows how to use the result of Google's SLAM solution, called Cartographer, to bootstrap our continuous-time SLAM algorithm. The presented approach optimizes the consistency of the global point cloud, and thus improves on Google's results. We use the algorithms and data from Google as input for our continuous-time SLAM software. We also successfully applied our software to a similar backpack system which delivers consistent 3D point clouds even in absence of an IMU.

Cite

CITATION STYLE

APA

Nüchter, A., Bleier, M., Schauer, J., & Janotta, P. (2017). Improving google’s cartographer 3D mapping by continuous-time slam. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives (Vol. 42, pp. 543–549). International Society for Photogrammetry and Remote Sensing. https://doi.org/10.5194/isprs-archives-XLII-2-W3-543-2017

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free