This session will provide an opportunity for attendees to learn about concrete challenges, technology trends and concrete application scenarios which are driving the FIWARE technical roadmap on robotics and automation technologies. The session will commence with an overview of the FIWARE approach to create and exploit synergies between Digital Twins and AI-driven robotics automation in the context of smart industry solutions for manufacturing, intralogistics, and agriculture sectors. Following that, the presentations will delve into real-world examples, emphasizing the potential benefits and limitations of Digital Twin approaches to smart solution development in concrete robotics contexts. Special emphasis will be put on showing how FIWARE based digital twins and robotics bring value into disruptive solutions for manufacturing execution and operations management, material flow automation, and efficient monitoring and supervision of smart agriculture environments such as green houses and insect farms. The interoperability between FIWARE-based digital twins and OPC UA robots is also a major topic in this session. To conclude, a wrap up presentation will summarize the take away messages, provide some insights into the future direction of this exciting technology, and discuss some relevant opportunities for establishing collaboration projects. Attendees will leave the session with a greater understanding of FIWARE-based Digital Twins in smart industry solutions, how they can be used to improve the performance and efficiency of robotic systems, and some of the most relevant initiatives of the FIWARE community in this domain.

1. Vienna, Austria
12-13 June, 2023
#FIWARESummit
From Data
to Value
OPEN SOURCE
OPEN STANDARDS
OPEN COMMUNITY
Optimization of Material Flows in Warehouses and
Smart Factory Floors
Peter Detzner
Fraunhofer Institute for Material Flow and Logistics

2. Images: Adobe Stock
[BtV14] Bauernhansl, Thomas; ten Hompel, Michael; Vogel-Heuser, Birgit: Industrie
4.0 in Produktion, Automatisierung Und Logistik: Anwendung, Technologien,
Migration. Wiesbaden: Springer Vieweg, 2014
[LDE+22]Lünsch, Dennis; Detzner, Peter; Ebner, Andreas; Kerner, Soren: SWAP-IT:
A Scalable and Lightweight Industry 4.0 Architecture for Cyber-Physical Production
Systems. In: 2022 IEEE 18th CASE, Mexico City, 2022
[Sta20] Statistisches Bundesamt: IoT Connected Devices Worldwide 2019-2030.
https: //www.statista.com/statistics/1183457/iot-connected-devices-worldwide/,
December 2020.
Motivation
The world is changing…
© Fraunhofer IML
6/20/2023
Slide 2
Supply Bottlenecks
Pandemic
Mass Production
Customized Products
[BtV14], [LDE22], [Sta20]
Flexibility
Functionality
Transparency
Robustness …
Scalability
(Re-)Configuration

3. Heterogeneous, Load-Optimized Robot Teams and Production Architectures
Use-Cases
 Production Scheduling
 Large numbers of
mobile robots
 Mobile robotic teams
 Mobile quality control
 Divide-Conquer
Production
 Manufacturing
Planning
 Stationary Robot-
Robot-Collaboration
 High repetition
11/29/22 © Fraunhofer IML
Page 3
Flexibility Cooperation Task Scheduling Timing
Swarm-based
Production
Airplane Production Large-Scale Production Precise-Production

4. SWAP-IT Architecture
A Fraunhofer LighthouseProject
A Scalable and Lightweight Industry 4.0 Architecture for Cyber-Physical Production Systems

5. Decentralized Autonomous Mobile Robot Control
ParadigmShift
From centralized towards decentralized control
20.06.2023 © Fraunhofer IML
Slide 5
Fleet Controller
Centralized Automated Guided Vehicles control

6. Autonomous Mobile Robots
20.06.2023 © Fraunhofer IML
Slide 6
Example Fraunhofer evoBOTTM
Robotic System are becoming more and more versatile Robot-Robot-Collaboration is coming more into focus

7. Simulation based
20.06.2023 © Fraunhofer IML
Slide 7

8. Adaptable
Production
Reference Architecture
20.06.2023 © Fraunhofer IML
Slide 8
Operational Level
FIWARE CONTEXT BROKER (NGSI API)
ERP SYSTEM HMI Sensors …
Adaptable
Production
Adaptable
Intralogistics
…
Adaptable Factory
SMART
DATA
MODELS
SMART
DATA
MODELS

9. Self-Organized [Ble17]
Icon and Figure: Franhofer IML
[Pla16a] Platform Industrie 4.0: Aspects of the Research Roadmap in Application Scenarios / Federal Ministry for Economic Affairs and Energy (BMWi).
[WJ95] Wooldridge, Michael; Jennings, Nicholas R.: Intelligent Agents: Theory and Practice. In: The Knowledge Engineering Review 10 (1995),
[Ble17] Blesing, Christian; Luensch, Dennis; Stenzel, Jonas; Korth, Benjamin: Concept of a Multi-agent Based Decentralized Production System for the Automotive Industry, The PAAMS Collection, 2017
Self-Organized Material Flow
Digital Representation of the Material Flow
20.06.2023 © Fraunhofer IML
Slide 9
Order-Centric Production and Logistic
[Pla16a]
Agent-based: Autonomous, Proactive,
Reactive, Interaction with Environment
[Wj95]

10. Self-Organized Material Flow
Initial Setup
6/20/2023 © Fraunhofer IML
Slide 10
Icons and Figures: Franhofer IML
Heterogenous AMRs
Precedence Graph with 9 Transport Orders
Temporal Constraints (Deadlines)

11. 20.06.2023 © Fraunhofer IML
Slide 11
Self-Organized Material Flow
Solution Space
Icons and Figures: Franhofer IML
Parameter P1 P2 P3 P4 P5 P6
Order Period
T in Seconds
78,75 63,75 37,5 26,25 17,5 8,75
Number AMRs 16 30 54 78 108 138
Number
Material Flows
8 10 17 24 34 66
Overall Number
of Participants
24 40 71 102 142 204
Valid
Invalid
Near-future prediction
Test in simulation before deployment
Number of AMRs
Order
Period
T
in
Seconds

12. Vienna, Austria
12-13 June, 2023
#FIWARESummit
Thanks!
Peter Detzner
Deputy Head of Department AI and Autonomous Systems
Fraunhofer Institute for Material Flow and Logistics
peter.detzner@iml.fraunhofer.de