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Flexible automation technologies often require an accuracy in the millimeter and milliradian range at different target positions. This thesis introduces a strategy that leverages a pose graph-based localization approach to reduce positioning errors at target poses of collaborating mobile robots. Using the precise localization from the pose graph we propose an odometry-based method to improve the accuracy at target locations, thus avoiding manual teach-in of reference scans for ICP that candoi:10.5281/zenodo.4742013 fatcat:637baqamlffkfda5cvvxzegyuy