Loop closure with a low power millimeter wave radar sensor using an autoencoder

Pieter Meiresone, David Van Hamme, Wilfried Philips

Keywords: FMCW, loop closure, deep learning, SLAM

Abstract:

In this paper, we will consider place recognition, more commonly know as loop closure, with a low
resolution single-chip millimeter wave (mmWave) radar in indoor environments. It is an essential
part in simultaneous localization and mapping (SLAM) systems to avoid drift. By using a novel method
to create descriptors or latent codes with an autoencoder in combination with exploiting the
temporal similarity between our latent codes, we are able to successfully extract loop closures with a
radar-only system without requiring ground truth. Our proposed method is validated in an industrial
IoT lab on an Unmanned Aerial Vehicle (UAV) and on a cargo bike in a parking building.

Submission Number: 41