Semantic Product Memory

Scientific Leader:
Project leader:
Dr. phil. Marc Ronthaler
Contact person:

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
Donee: German Research Center for Artificial Intelligence GmbH
Sponsor: Federal Ministry of Education and Research
Grant number: Federal Ministry of Education and Research (BMBF IKT 2020), grant no. 01IA08002

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
Related Robots: TelDaBot
Robot for telecommunication with RFID augmented infrastructure
Mobile Dual-Arm-Manipulation

Project details

MisterSemProM (Photo: Photo-Studio Blanck)
The SemProM-Head (Photo: Photo-Studio Blanck)
AILA (Rendering: David Grünwald, DFKI GmbH)

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.


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.


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: Autonomous product handling (SemProm)

AILA sorts out supermarket products using RFID information

SemProM: Semantic Product Memory

Example of the manipulation of complex and variable product packaging with smart labels and digital memories by robots

AILA: An autonomous, mobile dual-arm robot

The video shows the humanoid robot AILA performing object and scene recognition, as well as autonomous navigation and object grasping using digital product information stored in an RFID tag. 



A Robotic Platform for Building and Exploiting Digital Product Memories
Johannes Lemburg, Dennis Mronga, Achint Aggarwal, José de Gea Fernández, Marc Ronthaler, Frank Kirchner
In SemProM - Foundations of Semantic Product Memories for the Internet of Things, Springer, pages 91-106, May/2013. ISBN: 978-3-642-37376-3.
Supporting Interaction with Digital Product Memories
Alexander Kröner, Jens Haupert, José de Gea Fernández, Rainer Steffen, Christian Kleegrewe, Martin Schneider
In SemProM - Foundations of Semantic Product Memories for the Internet of Things, Springer, pages 223-242, May/2013. ISBN: 978-3-642-37376-3.


Conceptual and Embodiment Design of Robotic Prototypes
Johannes Lemburg, Frank Kirchner
Editors: Nikos Tsagarikis
In International Journal of Humanoid Robotics, World Scientific Publishing Co., volume 08, number 3/2011, pages 419-437, Nov/2011.
AILA - Design of an autonomous mobile dual-arm robot
Johannes Lemburg, José de Gea Fernández, Markus Eich, Dennis Mronga, Peter Kampmann, Andreas Vogt, Achint Aggarwal, Yuping Shi, Frank Kirchner
In Proceedings of IEEE International Conference on Robotics and Automation, (ICRA-11), 09.5.-15.5.2011, Shanghai, o.A., pages 5147-5153, May/2011. ISBN: 978-1-61284-380-3.
AILA - ein Dual-Arm Roboter für die Logistik
Marc Ronthaler, Achint Aggarwal, Dennis Mronga, Markus Eich
In Industrie Management - Zeitschrift für industrielle Geschäftsprozesse, GITO Verlag, volume 01/2011, pages 35-38, Feb/2011.


Design and Control of an Intelligent Dual-Arm Manipulator for Fault-Recovery in a Production Scenario
José de Gea Fernández, Johannes Lemburg, Thomas M. Roehr, Malte Wirkus, Iliya Gurov, Frank Kirchner
In ETFA'09 Proceedings of the 14th IEEE international conference on Emerging technologies & factory automation, (ETFA-09), 22.9.-26.9.2009, Mallorca, IEEE Press, pages 1583-1587, Sep/2009. ISBN: 978-1-4244-2727-7.

Back to the list of projects
last updated 21.08.2023
to top