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Romansy 16 pp 379-386 | Cite as

An Infrared Location System for Relative Pose Estimation of Robots

  • Anssi Kemppainen
  • Janne Haverinen
  • Juha Röning
Part of the CISM Courses and Lectures book series (CISM, volume 487)

Abstract

In this work we present an infrared location system for relative pose (position and orientation) estimation in a multi-robot system. Pose estimates are essential for tasks like cooperative simultaneous localization and mapping (C-SLAM), and formation control. In simultaneous localization and mapping (SLAM) relative pose estimates enable more accurate and less time-consuming map building. Respectively, formation control requires accurate pose estimates of other robots to enable robot cooperation in required formation. To address these challenging tasks for small-sized robots, we present a small-sized infrared location system with low current consumption. In the location system, robots use intensity and bearing measurements of received infrared signals to estimate the positions of other robots in polar coordinates. In addition, each robot has a unique modulation frequency from which they are recognized. The location system performs position estimation by rotating a beam collector at constant rotation speed and by measuring the bearing and intensity of the received signal. Infrared signals are received through a small aperture in the beam collector enabling accurate bearing measurements. In order to maximize the measurement range, infrared radiation is reflected sideways into a uniform zone using a conical mirror. Experiments were performed in a group of three robots with a measurement range of up to 3 m while the maximum number of robots was eight. The location system implemented enables relative position estimation among a group of small-sized robots without exchanging position estimates. This is advantageous since the robots are able to maintain formation also in the absence of a radio link.

Keywords

Mobile Robot Location System Simultaneous Localization Laser Range Finder Constant Rotation Speed 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© CISM, Udine 2006

Authors and Affiliations

  • Anssi Kemppainen
    • 1
  • Janne Haverinen
    • 1
  • Juha Röning
    • 1
  1. 1.Faculty of Technology, Department of Electrical and Information EngineeringUniversity of OuluOuluFinland

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