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
Nüchter, A., Bleier, M., Schauer, J., & Janotta, P. (2018). Continuous-Time SLAM—Improving Google’s Cartographer 3D Mapping. In Latest Developments in Reality-Based 3D Surveying and Modelling. MDPI. https://doi.org/10.3390/books978-3-03842-685-1-3
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.