Object-based differential Localization of Mobile Robots using sparse 2D Lidar Data

Abstract

The highly accurate pose estimation of mobile robots with respect to a known target object is a key technology for autonomous industrial manufacturing processes. Current approaches generally assume that the environment is static and locate the robot in relation to pre-defined positions. This paper presents an implementation and validation of how to localize a mobile robot in relation to the coordinate system of the target object - a prerequisite for any kind of manipulation or interaction. This allows the robot to be localized to arbitrarily positioned objects in the environment. For experimental validation, a high-precision external tracking system is used as ground truth. In this way, objects of different shapes are evaluated from different viewpoints. We achieve a pose estimation accuracy of less than 1 cm in a real world scenario.