GEN-SLAM: Generative Modeling for Monocular Simultaneous Localization and Mapping

Punarjay Chakravarty; Praveen Narayanan; Tom Roussel

ICRA 2019poster37 citations

GEN-SLAM: Generative Modeling for Monocular Simultaneous Localization and Mapping

Punarjay Chakravarty, Praveen Narayanan, Tom Roussel

Abstract

We present a Deep Learning based system for the twin tasks of localization and obstacle avoidance essential to any mobile robot. Our system learns from conventional geometric SLAM, and outputs, using a single camera, the topological pose of the camera in an environment, and the depth map of obstacles around it. We use a CNN to localize in a topological map, and a conditional VAE to output depth for a camera image, conditional on this topological location estimation. We demonstrate the effectiveness of our monocular localization and depth estimation system on simulated and real datasets.

BibTeX

@inproceedings{icra2019_genslamgenerativ,
  title = {GEN-SLAM: Generative Modeling for Monocular Simultaneous Localization and Mapping},
  author = {Punarjay Chakravarty and Praveen Narayanan and Tom Roussel},
  booktitle = {ICRA 2019},
  year = {2019}
}