Relative-absolute information for simultaneous localization and mapping
Journal
2007 IEEE International Conference on Robotics and Biomimetics
Pages
1641-1646
Date Issued
2007
Author(s)
Abstract
In this paper, a new algorithm, Relative-Absolute SLAM (RASLAM), is proposed to resolve the simultaneous localization and mapping problem. RASLAM utilizes relative and absolute information to estimate the robot pose and map in uncertain environment. Moreover, by combining different kinds of metric SLAM techniques, such as scanning matching, occupancy grid map, and feature-based SLAM, RASLAM can be applied to various unstructured surroundings. The experimental results show that RASLAM can achieve excellent performance even without odometry information in both outdoor and indoor environments.
SDGs
Type
conference paper