Map Building without Odometry Information

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.

Authors

• Francesco Amigoni
• Simone Gasparini
• Maria L. Gini

Keywords

• Buildings
• Mobile robots
• Robot sensing systems
• Computer science
• Scattering
• Resumes
• Simultaneous localization and mapping
• Robot localization
• Machinery
• Kalman filters
• Odometry Information
• Global Map
• Sequence Mapping
• Mobile Robot
• Part Of The Map
• Different Types Of Environments
• Sequencing Methods
• Final Map
• Geometric Features
• Computational Effort
• Time Instants
• Line Segment
• Matching Model
• Part Of Environment
• Tree Method
• Integration Of Sequences
• Environment Map
• Set Of Segments
• Least-squares Minimization
• Segment Pairs
• Difference Histogram
• Robot Pose
• Matching Segments