Most map building methods employed by mobile robots are based on the assumption that an estimate of robot poses can be obtained from odometry readings or from observing landmarks or other robots. In this paper we propose methods to build a global geometric map by integrating scans collected by laser range scanners without using any knowledge about the robots' poses. We consider scans that are collections of line segments. Our approach increases the flexibility in data collection, since robots do not need to see each other during mapping, and data can be collected by multiple robots or a single robot in one or multiple sessions. Experimental results show the effectiveness of our approach in different types of indoor environments.
Bibliographical noteFunding Information:
Manuscript received June 1, 2005; revised June 1, 2006. The work of F. Amigoni was supported in part by a Fulbright fellowship and by a Progetto Giovani Ricercatori 1999 grant. The work of M. Gini by the National Science Foundation under Grant EIA-0224363 and Grant EIA-0324864. F. Amigoni and S. Gasparini are with the Dipartimento di Elettronica e Informazione, Politecnico di Milano, Milano 20133, Italy (e-mail: firstname.lastname@example.org). M. Gini is with the Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455 USA (e-mail: email@example.com).
- Laser range scanners
- Map building
- Map merging
- Multirobot systems
- Scan matching