The project Semantic Product Memory (SemProM) aims at introducing a digital product memory for everyday items. In this context a mobile dual-arm robot is developed for the automatic manipulation and quality control of heterogeneous products. The digital product memory provides the robot with useful handling information as size, weight, lifting points, etc. of the targeted product. The project focuses on the combination of a highly flexible mobile manipulator with the optimal placement of a RFID antenna. The designed robot system will later be applied in areas of production and product distribution, where flexible product manipulation is required.
|Duration:||01.02.2008 till 31.01.2011|
|Grant number:||Federal Ministry of Education and Research (BMBF IKT 2020), grant no. 01IA08002|
|Partner:||Deutsches Forschungszentrum für Künstliche Intelligenz GmbH (Konsortialleitung), 7x4 Pharma GmbH, BMW Forschung und Technik GmbH, Deutsche Post AG, GLOBUS SB-Warenhaus Holding GmbH & Co. KG, SAP AG, Siemens AG|
|Application Field:||Logistics, Production and Consumer|
Robot for telecommunication with RFID augmented infrastructureAILA
The project Semantic Product Memory (SemProM) focuses on the development of a flexible mobile dual-arm robot, which adapts its behaviour to the specificities of the targeted product after extracting information from its digital product memory. The quality of logistic processes depends on the knowledge about the specific handling of a product during its transport. Currently, this information is not continuously available. In extreme cases this causes product damages in cases of complex transport processes with changing contract partners. The digital product memory can be used to store the necessary handling information for the transport of the product in machine-readable form. The handling information is thus directly connected to the product and is available at any time. This yields a high benefit for robot systems that manipulate products of varying shape. The gripper of the robot automatically adapts to the specifications provided by the digital product memory regarding size, weight, lifting points, etc. of the considered product. It also guarantees that constraints like maximum acceleration or geometric orientation are not violated.
In flexible and automatic manufacturing processes, different, non-uniform items are produced. The high amount of varying products demands for improved approaches of quality control. Classical control methods are insufficient here, since they are based on the detection of anomalies of the considered product compared to a given sample item. The digital product memory facilitates the storage of relevant parameters during the whole production process, allowing for conclusions regarding the quality of the considered product. If it is of inferior quality, the product can be removed from the production process at an early stage, improving the efficiency of the overall production process.
The mobile dual-arm robot is the first system comprising flexible grippers combined with optimally placed RFID antennae. The digital product memory is read by the antenna and determines the optimal configuration of the grippers. In order to establish full Cartesian positioning together with the ability to cope with obstacles, every arm of the robot has seven degrees of freedom. The robot will automatically navigate and localize itself in a factory production hall and automatically approach a recharging station when its battery power drops below a critical value. It will also be able to communicate with other components and users in the environment. Additionally, it is intended to store a summary of the actual product manipulations performed by the robot in the digital product memory.
AILA: Autonomes Produktabwicklung (SemProm)
AILA benutzt RFID Informationen um Artikel aus dem Supermarkt zu sortieren.
SemProM: Semantic Product Memory
Beispiel der Manipulation von komplexen und variablen Produktverpackungen mit Smart Labels und digitalen Gedächtnissen durch Roboter.
AILA: Ein autonomer, mobiler Dual-Arm-Roboter
Dieses Video zeigt die Durchführung von Objekt- und Szenenerkennung des humanoiden Roboters AILA, sowie eine autonome Navigation und Objekterfassung unter Verwendung digitaler Produktinformationen, die in einem RFID-Tag gespeichert sind.