University of Surrey

Test tubes in the lab Research in the ATI Dance Research

SeDAR – Semantic Detection and Ranging: Humans can localise without LiDAR, can robots?

Mendez Maldonado, Oscar, Hadfield, Simon, Pugeault, Nicolas and Bowden, Richard (2018) SeDAR – Semantic Detection and Ranging: Humans can localise without LiDAR, can robots? In: 2018 IEEE International Conference on Robotics and Automation, 21-25 May 2018, Brisbane, Australia.

SeDAR – Semantic Detection and Ranging.pdf - Accepted version Manuscript

Download (1MB) | Preview


How does a person work out their location using a floorplan? It is probably safe to say that we do not explicitly measure depths to every visible surface and try to match them against different pose estimates in the floorplan. And yet, this is exactly how most robotic scan-matching algorithms operate. Similarly, we do not extrude the 2D geometry present in the floorplan into 3D and try to align it to the real-world. And yet, this is how most vision-based approaches localise. Humans do the exact opposite. Instead of depth, we use high level semantic cues. Instead of extruding the floorplan up into the third dimension, we collapse the 3D world into a 2D representation. Evidence of this is that many of the floorplans we use in everyday life are not accurate, opting instead for high levels of discriminative landmarks. In this work, we use this insight to present a global localisation approach that relies solely on the semantic labels present in the floorplan and extracted from RGB images. While our approach is able to use range measurements if available, we demonstrate that they are unnecessary as we can achieve results comparable to state-of-the-art without them.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
Mendez Maldonado,
Date : 25 May 2018
DOI : 10.1109/ICRA.2018.8461074
Copyright Disclaimer : © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Related URLs :
Depositing User : Clive Harris
Date Deposited : 19 Mar 2018 13:52
Last Modified : 26 Oct 2018 10:13

Actions (login required)

View Item View Item


Downloads per month over past year

Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800