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Journal of Sensors
Volume 2017, Article ID 4853915, 16 pages
Research Article

Projection Surfaces Detection and Image Correction for Mobile Robots in HRI

Departamento de Sistemas y Automática, Universidad Carlos III de Madrid, 28911 Madrid, Spain

Correspondence should be addressed to José Carlos Castillo; se.m3cu.gni@litsacoj

Received 1 March 2017; Revised 22 May 2017; Accepted 4 June 2017; Published 12 July 2017

Academic Editor: Eugenio Martinelli

Copyright © 2017 Enrique Fernández-Rodicio et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Projectors have become a widespread tool to share information in Human-Robot Interaction with large groups of people in a comfortable way. Finding a suitable vertical surface becomes a problem when the projector changes positions when a mobile robot is looking for suitable surfaces to project. Two problems must be addressed to achieve a correct undistorted image: (i) finding the biggest suitable surface free from obstacles and (ii) adapting the output image to correct the distortion due to the angle between the robot and a nonorthogonal surface. We propose a RANSAC-based method that detects a vertical plane inside a point cloud. Then, inside this plane, we apply a rectangle-fitting algorithm over the region in which the projector can work. Finally, the algorithm checks the surface looking for imperfections and occlusions and transforms the original image using a homography matrix to display it over the area detected. The proposed solution can detect projection areas in real-time using a single Kinect camera, which makes it suitable for applications where a robot interacts with other people in unknown environments. Our Projection Surfaces Detector and the Image Correction module allow a mobile robot to find the right surface and display images without deformation, improving its ability to interact with people.