Passive wheels – A new localization system for automated guided vehicles

Abstract

This article introduces passive wheels as the new localization system for automated guided vehicles (AGVs). The article focuses on investigating the accuracy of the proposed system and comparing with other widely used solutions: rotary encoders coupled with drive wheels, AHRS and LiDAR scanner. The fusion of dead reckoning and inertial data is acquired by the implementation of the Kalman filter. On the other hand, the fusion of LiDAR data depends on application of the AMCL or the graph-based algorithm. The study was conducted on five different scenarios, designed to investigate the influence of specific types of movements on the performance of tested localization methods. Results indicate, that passive wheels dead reckoning outperforms drive wheels dead reckoning in most scenarios, minimizing errors due to reduced both longitudal and lateral slippages, which appear during AGV accelerating, decelerating and turning. AHRS integration improves accuracy, especially in scenarios involving significant amount of angular motion. LiDAR-based methods in short term show mediocre results, due to relatively high, but steady values of error. The study highlights the importance of the map's quality for LiDAR-based techniques and points up the conditions, under which the LiDAR-based techniques do not operate very well. In conclusion, the research provides insights into the strengths and weaknesses of various AGV localization techniques in various movement scenarios, emphasizing the impact of sensor choice and path-shape conditions on accuracy.

Keywords

• AGV
• Mobile robots
• Localization
• Dead reckoning