  This article addresses the localization problem in robotic autonomous luggage
trolley collection at airports and provides a systematic evaluation of
different methods to solve it. The robotic autonomous luggage trolley
collection is a complex system that involves object detection, localization,
motion planning and control, manipulation, etc. Among these components,
effective localization is essential for the robot to employ subsequent motion
planning and end-effector manipulation because it can provide a correct goal
position. In this article, we survey four popular and representative
localization methods to achieve object localization in the luggage collection
process, including radio frequency identification (RFID), Keypoints,
ultrawideband (UWB), and Reflectors. To test their performance, we construct a
qualitative evaluation framework with Localization Accuracy, Mobile Power
Supplies, Coverage Area, Cost, and Scalability. Besides, we conduct a series of
quantitative experiments regarding Localization Accuracy and Success Rate on a
real-world robotic autonomous luggage trolley collection system. We further
analyze the performance of different localization methods based on experiment
results, revealing that the Keypoints method is most suitable for indoor
environments to achieve the luggage trolley collection.
