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Indoor Real-Time Localisation for Multiple Autonomous Vehicles Fusing Vision, Odometry and IMU Data

  • Alessandro FaralliEmail author
  • Niko Giovannini
  • Simone Nardi
  • Lucia Pallottino
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9991)

Abstract

Due to the increasing usage of service and industrial autonomous vehicles, a precise localisation is an essential component required in many applications, e.g. indoor robot navigation. In open outdoor environments, differential GPS systems can provide precise positioning information. However, there are many applications in which GPS cannot be used, such as indoor environments. In this work, we aim to increase robot autonomy providing a localisation system based on passive markers, that fuses three kinds of data through extended Kalman filters. With the use of low cost devices, the optical data are combined with other robots’ sensor signals, i.e. odometry and inertial measurement units (IMU) data, in order to obtain accurate localisation at higher tracking frequencies. The entire system has been developed fully integrated with the Robotic Operating System (ROS) and has been validated with real robots.

Keywords

Localisation indoor Odometry IMU EKF Passive marker 

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Alessandro Faralli
    • 1
    Email author
  • Niko Giovannini
    • 1
  • Simone Nardi
    • 1
  • Lucia Pallottino
    • 1
  1. 1.Research Center E. Piaggio, Faculty of EngineeringUniversity of PisaPisaItaly

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