Renz, Matthias JohannesMatthias JohannesRenzRose, Hendrik WilhelmHendrik WilhelmRoseZiegenbein, JustinJustinZiegenbeinBraun, Philipp MaximilianPhilipp MaximilianBraun2025-01-232025-01-232024-10-30Logistics Journal 2024 (20): (2024-10-30)https://tore.tuhh.de/handle/11420/53488Autonomous mobile robots (AMR) have substantial impact on the automation of logistics processes like last mile delivery. In order to securely enter or interact with objects, accurate positioning of the object in the robot’s maps is required. If a large object is semi-static, occupies a large part of the surrounding and is previously known, different localization approaches can be used for positioning the object relative to the AMR. This contribution compares approaches for the position of semi-static objects in an AMR’s map such as AMCL, ICP and AprilTag detection using the robot’s LiDAR and cam-eras. It also develops an evaluation scheme to rate the approaches qualitatively and quantitatively to choose the most appropriate solution for the use case in hand. Based on the rating scheme, AprilTag localization proved to be the best performer for a last mile delivery robot entering a carrier vehicle.en2192-9084202420Wissenschaftliche Gesellschaft fur Technische LogistikAutonomous Mobile Robots (AMR) | Localization | real-world research | Semistatic ObstaclesSocial Sciences::388: TransportationTechnology::620: EngineeringJournal Article10.2195/lj_proc_renz_en_202410_01Journal Article