For both robots and humans to share an close environment, robots needs sensors for the measurement and detection of obstacles. They need also the capability to interact with this obstacles on the environment. For this, robots must  maintain his correct position and the correct position of obstacles in unknown and dynamic environment. 

Localization is an important problem in autonomous mobile robots navigation. This project aims to contribute in the development of an Navigation and Localization architecture.  It describes a full implementation of the extended Kalman filter (EKF) for the simultaneous localization and map building (SLAM) with line features with a Nomad 200 Mobile Robot.

SLAM is the problem of an autonomous vehicle starting at an unknown position which then builds a map step by step and computes its absolute position according to the map.


  • 2006-03-24 -  Site launched
  • 2006-04-30 -  Software available in