A Systematic Evaluation of Different Indoor Localization Methods in Robotic Autonomous Luggage Trolley Collection at Airports

TL;DR

The paper addresses indoor localization for robotic autonomous luggage trolley collection at airports. It systematically evaluates four indoor localization methods—RFID, Keypoints, UWB, and Reflectors—using a designed evaluation framework and real-world experiments. The results show Reflectors offer the highest accuracy but face deployment challenges, while Keypoints provide the best practical balance for typical indoor airport environments, making it the most suitable choice overall. The work provides actionable guidance for designing indoor localization in airport robotics and lays groundwork for real-world deployment validation.

Abstract

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.

Figures (9)

• Figure 1: Different localization methods in robotic autonomous luggage trolley collection.
• Figure 2: The schematic diagram of the RFID method.
• Figure 3: The schematic diagram of the Keypoints method.
• Figure 4: The schematic diagram of the UWB method.
• Figure 5: The schematic diagram of the Reflectors method.