Leg Detection and Tracking for a Mobile Robot and Based on a Laser Device, Supervised Learning and Particle Filtering

  • Eugenio Aguirre
  • Miguel Garcia-Silvente
  • Javier Plata
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 252)


People detection and tracking is an essential skill to obtain social and interactive robots. Computer vision has been widely used to solve this task but images are affected by noise and illumination changes. Laser range finder is robust against illumination changes so that it can bring useful information to carry out the detection and tracking. In fact, multisensor approaches are showing the best results. In this work, we present a new method to detect and track people using a laser range finder. Patterns of leg are learnt from 2d laser data using supervised learning. Unlike others leg detection approaches, people can be still or moving at the surroundings of the robot. The method of leg detection is used as observation model in a particle filter to track the motion of a person. Experiments in a real indoor environment have been carried out to validate the proposal.


Leg detection and tracking laser range finder supervised learning particle filter mobile robots 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Eugenio Aguirre
    • 1
  • Miguel Garcia-Silvente
    • 1
  • Javier Plata
    • 1
  1. 1.Department of Computer Science and A.I., CITIC-UGR E.T.S. Ingenierías en Informática y en TelecomunicacionesUniversity of GranadaGranadaSpain

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