Research Article
Docking autonomous robots in passive docks with Infrared sensors and QR codes
@ARTICLE{10.4108/icst.tridentcom.2015.259673, author={Roberto Quilez and Adriaan Zeeman and Nathalie Mitton and Julien Vandaele}, title={Docking autonomous robots in passive docks with Infrared sensors and QR codes}, journal={EAI Endorsed Transactions on Self-Adaptive Systems}, volume={1}, number={2}, publisher={EAI}, journal_a={SAS}, year={2015}, month={8}, keywords={testbed, experimentation, docking, robots, qrcode}, doi={10.4108/icst.tridentcom.2015.259673} }
- Roberto Quilez
Adriaan Zeeman
Nathalie Mitton
Julien Vandaele
Year: 2015
Docking autonomous robots in passive docks with Infrared sensors and QR codes
SAS
EAI
DOI: 10.4108/icst.tridentcom.2015.259673
Abstract
In this paper, we describe an inexpensive and easy to deploy docking solution in passive charging docks for autonomous mobile robots. The objective is to achieve long-term autonomous robots within an experiment test-bed. We propose to combine the use of QR codes as landmarks and Infrared distance sensors. The relative size of the lateral edges of the visual pattern is used to position the robot in relation with the dock. Infrared distance sensors are then used to perform different approaching strategies depending on the distance. Experiments show that the proposed solution is fully operational and robust. Not to rely exclusively on visual pattern recognition avoids potential errors induced by camera calibration. Additionally, as a positive side effect, the use of Infrared sensors allows the robot to avoid obstacles while docking. The finality of such an approach is to integrate these robots into the FIT IoT Lab experimental testbed which allows any experimenter to book wireless resources such as wireless sensors remotely and to test their own code. Wifibots holding wireless sensors will be integrated as additional reservable resources of the platform to enlarge the set of possible experimentations with mobile entities.
Copyright © 2015 R. Quilez et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.