Method for Specifying Location Data Requirements for Intralogistics Applications
Various applications leverage location data to increase transparency, efficiency, and safety in intralogistics. There are several properties of location data, such as the data's degrees of freedom, system latency, update rate, or accuracy. To select a suitable indoor localization system, corresponding data requirements must be derived by analyzing the considered application. To date, the dependencies of the system performance and location data requirements have not been satisfactorily described in the literature. Thus, no method exists to adequately derive location data requirements. For intralogistics, such a method is of particular relevance due to the high-cost sensitivity and heterogeneity of partially safety-relevant indoor localization applications. To fill this gap, a method for selecting and quantifying location data requirements for the application in intralogistics is presented in this work, creating substantial added value for warehouse managers and system integrators. The method is based on a spatial model that is built on the premise that location data is used to determine the presence or absence of an entity in a multidimensional interest space. The usage of the method is demonstrated in an exemplary case study for the application of 'Automated Pallet Booking'.
Code (0)
등록된 구현이 없습니다.
Tasks
Indoor LocalizationSimilar Papers 제목 키워드 기반
Allocation of Multi-Robot Tasks with Task Variants
Task allocation has been a well studied problem. In most prior problem formulations, it is assumed that each task is associated with a unique set of resource requirements. In the scope of multi-robot task allocation prob…
Industrial Segment Anything -- a Case Study in Aircraft Manufacturing, Intralogistics, Maintenance, Repair, and Overhaul
Deploying deep learning-based applications in specialized domains like the aircraft production industry typically suffers from the training data availability problem. Only a few datasets represent non-everyday objects, s…
MARLIN: A Cloud Integrated Robotic Solution to Support Intralogistics in Retail
In this paper, we present the service robot MARLIN and its integration with the K4R platform, a cloud system for complex AI applications in retail. At its core, this platform contains so-called semantic digital twins, a …
Autonomous NavigationTask PlanningVision-Language Model Reasoning for Contextual Semantic Mapping in Intralogistics
Autonomous mobile robots operating in intralogistics environments rely on geometric maps for localization and navigation, but lack semantic understanding of objects and their contextual properties. We present a contextua…
Instance SegmentationEfficient Human-Aware Task Allocation for Multi-Robot Systems in Shared Environments
Multi-robot systems are increasingly deployed in applications, such as intralogistics or autonomous delivery, where multiple robots collaborate to complete tasks efficiently. One of the key factors enabling their efficie…