Map Building without Odometry Information

Francesco Amigoni (1) , Simone Gasparini (1, 2) , Maria Gini (3)

1 AIRLab - Artificial Intelligent and Robotics Laboratory
2 DEI - Dipartimento di Elettronica e Informazione
3 Department of Computer Science and Engineering [Minneapolis]

The map building methods usually employed by mobile robots are based on the assumption that an estimate of the position of the robot can be obtained from odometry readings. In this paper we propose three methods that build a geometrical global map by integrating partial maps without using any odometry information. We focus on the problem of integrating a sequence of partial maps that specifies the order in which the partial maps must be integrated. Experimental results show the effectiveness of our approach in different types of environments.

Domaines: Intelligence artificielle [cs.AI]; Robotique [cs.RO]

Francesco Amigoni, Simone Gasparini, Maria Gini. Map Building without Odometry Information. Proceedings of the 2004 IEEE International Conference on Robotics and Automation, ICRA 2004, Apr 2004, New Orleans, LA, United States. pp.3753--3758, ⟨10.1109/ROBOT.2004.1308853⟩. ⟨hal-00818500⟩