Deep Learning Applications in Simultaneous Localization and Mapping

3Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.

Abstract

Simultaneous Location and Mapping (SLAM) is a research hotspot in the field of intelligent robots in recent years. Its processing object is the visual image. Deep learning has achieved great success in the field of computer vision, which makes the combination of deep learning and slam technology a feasible scheme. This paper summarizes some applications of deep learning in SLAM technology and introduces its latest research results. The advantages and disadvantages of deep-learning-based-SLAM technology are compared with those of traditional SLAM. Finally, the future development direction of SLAM plus deep learning technology is prospected.

Cite

CITATION STYLE

APA

Zhang, H. (2022). Deep Learning Applications in Simultaneous Localization and Mapping. In Journal of Physics: Conference Series (Vol. 2181). IOP Publishing Ltd. https://doi.org/10.1088/1742-6596/2181/1/012012

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