Improving Robot Self-localization Using Landmarks' Poses Tracking and Odometry Error Estimation

In this article the classical self-localization approach is improved by estimating, independently from the robot’s pose, the robot’s odometric error and the landmarks’ poses. This allows using, in addition to fixed landmarks, dynamic landmarks such as temporally local objects (mobile objects) and spatially local objects (view-dependent objects or textures), for estimating the odometric error, and therefore improving the robot’s localization. Moreover, the estimation or tracking of the fixed-landmarks’ poses allows the robot to accomplish successfully certain tasks, even when having high uncertainty in its localization estimation (e.g. determining the goal position in a soccer environment without directly seeing the goal and with high localization uncertainty). Furthermore, the estimation of the fixed-landmarks’ pose allows having global measures of the robot’s localization accuracy, by comparing the real map, given by the real (a priori known) position of the fixed-landma...

• Type: Conference
• Year: 2007
• Where: ROBOCUP
• Authors: Pablo Guerrero, Javier Ruiz-del-Solar
• Keywords: Odometric Error, ROBOCUP 2007, Robot’s Localization, Robot’s Odometric Error