Learning globally consistent maps by relaxation
- 24 April 2000
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 4 (10504729) , 3841-3846
- https://doi.org/10.1109/robot.2000.845330
Abstract
Mobile robots require the ability to build their own maps to operate in unknown environments. A fundamental problem is that odometry-based dead reckoning cannot be used to assign accurate global position information to a map because of drift errors caused by wheel slippage. The paper introduces a fast, online method of learning globally consistent maps, using only local metric information. The approach differs from previous work in that it is computationally cheap, easy to implement and is guaranteed to find a globally optimal solution. Experiments are presented in which large, complex environments were successfully mapped by a real robot, and quantitative performance measures are used to assess the quality of the maps obtained.Keywords
This publication has 9 references indexed in Scilit:
- Knowing your place in real world environmentsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Elastic correction of dead-reckoning errors in map buildingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- "OXNAV": reliable autonomous navigationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Exploration of unknown environments using a compass, topological map and neural networkPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1999
- Mobile robot self-localisation and measurement of performance in middle-scale environmentsRobotics and Autonomous Systems, 1998
- A Probabilistic Approach to Concurrent Mapping and Localization for Mobile RobotsMachine Learning, 1998
- Self-Orienting with On-Line Learning of Environmental FeaturesAdaptive Behavior, 1998
- Globally Consistent Range Scan Alignment for Environment MappingAutonomous Robots, 1997
- Directed Sonar Sensing for Mobile Robot NavigationPublished by Springer Nature ,1992