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1
Christian Henkel
© Fraunhofer IPA 2017
An Overview
Cloud Robotics @ IPA
2
Christian Henkel
© Fraunhofer IPA 2017
Cloud Picking
3
Christian Henkel
© Fraunhofer IPA 2017
Griff in die Kiste
 3D Scan der Teile
 Upload zu Cloud Server
 Berechnung Griffmöglichkeit
 Greifen
 Monitoring
 Rechenleistung skalierbar
 Zentralisierte CAD Definition
 Robustheit durch Zentrales Monitoring
4
Christian Henkel
© Fraunhofer IPA 2017
Griff in die Kiste - as a service
 Rechenleistung skalierbar
 Zentralisierte CAD Definition
 Robustheit durch Zentrales Monitoring
 Prozessoptimierung
 Qualitätsoptimierung
 Immer aktuellste Software Version
Bin-Picking App
Object localization
Task/Path planning
Work piece CAD-modelPlanner
Portal
System planning
Part teaching
Operator
Object
Features
Motion
Data
Actors
Skills, Services
Sensor
Part models
5
Christian Henkel
© Fraunhofer IPA 2017
Big Robot Data
BÄR Automation GmbH
6
Christian Henkel
© Fraunhofer IPA 2017
Laser Scanner
Camera
Load Sensors
MSB
AGV
Database
Registeras
application
DataStream
e.g.OPCUA
Registeras
smartobject
Environment
Sense
Clustering per AGV
 Predictive Maintenance
Clustering per Environment
 Localization Improvement
DataStream
e.g.WebSocket
Big Robot Data
Architektur
Image: © BÄR Automation GmbH, CC-BY-SA 4.0
7
Christian Henkel
© Fraunhofer IPA 2017
Clustering per AGV
• Multiple AGVs
• Clustering based on performance
characteristics
• Identification of improvement potentials
• Predictive Maintenance
Clustering on Area
• Shop floor mapping
• MapReduce to identify areas
• Improvement where
• Delays
• Bad localization
• Improvements of Shop Floor
Big Robot Data
Analysis
8
Christian Henkel
© Fraunhofer IPA 2017
Cloud Navigation
9
Christian Henkel
© Fraunhofer IPA 2017
Cloud Navigation
10
Christian Henkel
© Fraunhofer IPA 2017
Architecture
 Holistic Environment Model
 Global Planning
 External Sensors / Localization
 Cost Scaling Sensors / Computation
11
Christian Henkel
© Fraunhofer IPA 2017
Sensor Upgrade as a Service
Unknown Obstacle External Sensor
 Robot can not perceive the obstacle
 Will only replan if obstacle is in sight
 External sensor can perceive the obstacle
 Robot will immediately replan
Sensor
Integration
Service
Goal
New Path
12
Christian Henkel
© Fraunhofer IPA 2017
Modular Intelligent Intralogistics
Fleet Control
13
Christian Henkel
© Fraunhofer IPA 2017
Linear Production vs Flexible Production
Motivation
?
14
Christian Henkel
© Fraunhofer IPA 2017
Challenges in Flexible Production
Motivation
 No artificial navigation infrastructure
 No magnetic guidance
 No reflectors
 No predefined route map
 Vehicles can take any route
 Highly dynamic obstacles
 Workers
 No allocation of tasks
 Any AGV can take any transport task
?
15
Christian Henkel
© Fraunhofer IPA 2017
Problem Definition
Architecture
Job Source
e. g. MES
AGV1 AGV3 AGV4AGV2
…
Planner
SmartLeitstand
Job1: A → B
Job2: C → A
Job1: A → B Job2: C → A
16
Christian Henkel
© Fraunhofer IPA 2017
Planning set up
Architecture
Job Source
e. g. MES
AGV1 AGV3 AGV4AGV2
…
Job1: A → B
Job2: C → A
Path: A → B Path: C → A
Model Building PlanningModel
17
Christian Henkel
© Fraunhofer IPA 2017
 Record of all past jobs with
 Time of Receiving
 Start and Goal
 Prediction
 Based on past jobs
 Predictive modelling of task time
 If an AGV is free
 Can already go to start
 Move in area of multiple possible tasks
 Decisions for task allocation
Job Prediction
Probabilistic Task Model
18
Christian Henkel
© Fraunhofer IPA 2017
Conflict Based Search
Task Allocation
19
Christian Henkel
© Fraunhofer IPA 2017
Conflict Based Search
Task Allocation
 Example of tasks
 Agent locations
 Idle goals
 Solution with time as
vertical axis
20
Christian Henkel
© Fraunhofer IPA 2017
 Converting occupancy grid map
 into graph for planning
 No collison
 Optimized for motion
 Fully connected
 Population of possible poses
 Locations
 Rotations
 Connections
Multi agent navigation in open space
Probabilistic roadmap
21
Christian Henkel
© Fraunhofer IPA 2017
SuperCaps in AGVs
22
Christian Henkel
© Fraunhofer IPA 2017
Autonomous Guided Vehicles
Supercapacitor equipped AGVs
Traditional Batteries
 High Capacity
 Long Charging
 Idle times while charging
 Unused capital (AVGs)
Supercapacitors
 Medium Capacity
 Fast Charging
 Can charge in transfer times
 Idle times occurring anyway
23
Christian Henkel
© Fraunhofer IPA 2017
Basic
Services
Aggregated
Services
Services
Integration
Services
Equipment
& CPS
VFK Marketplace
App1 App2 ...
Devices VFK SDK
Cloud-based Charging Control
Supercapacitor equipped AGVs
Cloud Server
 Monitoring state of charge
 Control of charging stations
 Energy Optimization
 Intelligent planning of charge times
 Integration with production control
Smart Objects
 AGVs
 Charging Stations
24
Christian Henkel
© Fraunhofer IPA 2017
Charge-Level-Aware Task Allocation
Supercapacitor equipped AGVs
Transport Task
Manufacturing Station
AGV
Manufacturing Station with Charging
25
Christian Henkel
© Fraunhofer IPA 2017
MRK für körperlich
beeinträchtige Menschen
26
Christian Henkel
© Fraunhofer IPA 2017
Datenflüsse jetzt
WT SensorAktuator
Tischhöhe
MRK Roboter
Warn-/Fehlercodes
Schließen/Öffnen
WTvorhanden
AnzahlDüsen
WT Blocker
Integrierte
Kamera
27
Christian Henkel
© Fraunhofer IPA 2017
RFID-
Leser
Datenflüsse erweitert
Kamera
Mikrofon
Display
Bilderfassung
Spracherkennung
Personenidentifikation
Arbeitsanweisungen
28
Christian Henkel
© Fraunhofer IPA 2017
Skill-based Assembly
29
Christian Henkel
© Fraunhofer IPA 2017
Basic
Services
Aggregated
Services
Services
Integration
Services
Equipment
& CPS
VFK Marketplace
App1 App2 ...
Devices VFK SDK
Intelligente Montage
Nieten, Schrauben, Klipsen. Viele Anwendungen. Eine Lösung.
 Cloudbasierte Ablage Montageaufgaben
 Laden der nötigen Unteraufgaben
 Durchführung auf beliebigem Roboter
 Programmierung in Cloud
 Plattformunabhängig
 Zentrale Ablage
 Serviceorientierte Geschäftsmodelle
30
Christian Henkel
© Fraunhofer IPA 2017
Komponenten
 Beliebige Roboter
 Integration via MSB
 Wartung als Service
 ggf. Bereitstellung
 PiTask
 Verwaltung von Montage-“skills“
 Konfiguration
 Steuerung Roboter
 Monitoring
31
Christian Henkel
© Fraunhofer IPA 2017
Time Sensitive Networks
32
Christian Henkel
© Fraunhofer IPA 2017
Distributed Robotic Systems
Application in Robotics
Synchronisation
Ethernet Communication
TSN Communication
Non-Critical Node
e.g. Planning
Time-Critical Node
e.g. Motion Control
Internal Clock
e.g. ROS Time
Non-Critical Node
e.g. Task Execution
Time-Critical Node
e.g. Drive
Internal Clock
e.g. ROS Time
33
Christian Henkel
© Fraunhofer IPA 2017
Use Cases: Control by Wire
Time-Sensitive Networking
AGV
Position
Sensor
Cooperative
Task
Omnidirectional
Drive
34
Christian Henkel
© Fraunhofer IPA 2017
Use Cases: Control by Wire
Time-Sensitive Networking
Cloud
Controller
Target
Position
Disturbance
Feedback
Positioning
Localization
35
Christian Henkel
© Fraunhofer IPA 2017
Use Cases: Control by Wire
Time-Sensitive Networking
Cloud
Controller
Target
Position
Disturbance
Feedback
Positioning
Localization
= Problems
if high
Latency
36
Christian Henkel
© Fraunhofer IPA 2017
Christian Henkel M.Sc.
Project Manager
Competence Centre Digital Tools for Manufacturing
Tel.: +49 (0) 711 970-1331
christian.henkel@ipa.fraunhofer.de
www.ipa.fraunhofer.de
Fraunhofer IPA
Contact
Future is our product
Sustainable. Personalized. Smart.
Care-O-bot® 4

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Cloud Robotics

  • 1. 1 Christian Henkel © Fraunhofer IPA 2017 An Overview Cloud Robotics @ IPA
  • 2. 2 Christian Henkel © Fraunhofer IPA 2017 Cloud Picking
  • 3. 3 Christian Henkel © Fraunhofer IPA 2017 Griff in die Kiste  3D Scan der Teile  Upload zu Cloud Server  Berechnung Griffmöglichkeit  Greifen  Monitoring  Rechenleistung skalierbar  Zentralisierte CAD Definition  Robustheit durch Zentrales Monitoring
  • 4. 4 Christian Henkel © Fraunhofer IPA 2017 Griff in die Kiste - as a service  Rechenleistung skalierbar  Zentralisierte CAD Definition  Robustheit durch Zentrales Monitoring  Prozessoptimierung  Qualitätsoptimierung  Immer aktuellste Software Version Bin-Picking App Object localization Task/Path planning Work piece CAD-modelPlanner Portal System planning Part teaching Operator Object Features Motion Data Actors Skills, Services Sensor Part models
  • 5. 5 Christian Henkel © Fraunhofer IPA 2017 Big Robot Data BÄR Automation GmbH
  • 6. 6 Christian Henkel © Fraunhofer IPA 2017 Laser Scanner Camera Load Sensors MSB AGV Database Registeras application DataStream e.g.OPCUA Registeras smartobject Environment Sense Clustering per AGV  Predictive Maintenance Clustering per Environment  Localization Improvement DataStream e.g.WebSocket Big Robot Data Architektur Image: © BÄR Automation GmbH, CC-BY-SA 4.0
  • 7. 7 Christian Henkel © Fraunhofer IPA 2017 Clustering per AGV • Multiple AGVs • Clustering based on performance characteristics • Identification of improvement potentials • Predictive Maintenance Clustering on Area • Shop floor mapping • MapReduce to identify areas • Improvement where • Delays • Bad localization • Improvements of Shop Floor Big Robot Data Analysis
  • 8. 8 Christian Henkel © Fraunhofer IPA 2017 Cloud Navigation
  • 9. 9 Christian Henkel © Fraunhofer IPA 2017 Cloud Navigation
  • 10. 10 Christian Henkel © Fraunhofer IPA 2017 Architecture  Holistic Environment Model  Global Planning  External Sensors / Localization  Cost Scaling Sensors / Computation
  • 11. 11 Christian Henkel © Fraunhofer IPA 2017 Sensor Upgrade as a Service Unknown Obstacle External Sensor  Robot can not perceive the obstacle  Will only replan if obstacle is in sight  External sensor can perceive the obstacle  Robot will immediately replan Sensor Integration Service Goal New Path
  • 12. 12 Christian Henkel © Fraunhofer IPA 2017 Modular Intelligent Intralogistics Fleet Control
  • 13. 13 Christian Henkel © Fraunhofer IPA 2017 Linear Production vs Flexible Production Motivation ?
  • 14. 14 Christian Henkel © Fraunhofer IPA 2017 Challenges in Flexible Production Motivation  No artificial navigation infrastructure  No magnetic guidance  No reflectors  No predefined route map  Vehicles can take any route  Highly dynamic obstacles  Workers  No allocation of tasks  Any AGV can take any transport task ?
  • 15. 15 Christian Henkel © Fraunhofer IPA 2017 Problem Definition Architecture Job Source e. g. MES AGV1 AGV3 AGV4AGV2 … Planner SmartLeitstand Job1: A → B Job2: C → A Job1: A → B Job2: C → A
  • 16. 16 Christian Henkel © Fraunhofer IPA 2017 Planning set up Architecture Job Source e. g. MES AGV1 AGV3 AGV4AGV2 … Job1: A → B Job2: C → A Path: A → B Path: C → A Model Building PlanningModel
  • 17. 17 Christian Henkel © Fraunhofer IPA 2017  Record of all past jobs with  Time of Receiving  Start and Goal  Prediction  Based on past jobs  Predictive modelling of task time  If an AGV is free  Can already go to start  Move in area of multiple possible tasks  Decisions for task allocation Job Prediction Probabilistic Task Model
  • 18. 18 Christian Henkel © Fraunhofer IPA 2017 Conflict Based Search Task Allocation
  • 19. 19 Christian Henkel © Fraunhofer IPA 2017 Conflict Based Search Task Allocation  Example of tasks  Agent locations  Idle goals  Solution with time as vertical axis
  • 20. 20 Christian Henkel © Fraunhofer IPA 2017  Converting occupancy grid map  into graph for planning  No collison  Optimized for motion  Fully connected  Population of possible poses  Locations  Rotations  Connections Multi agent navigation in open space Probabilistic roadmap
  • 21. 21 Christian Henkel © Fraunhofer IPA 2017 SuperCaps in AGVs
  • 22. 22 Christian Henkel © Fraunhofer IPA 2017 Autonomous Guided Vehicles Supercapacitor equipped AGVs Traditional Batteries  High Capacity  Long Charging  Idle times while charging  Unused capital (AVGs) Supercapacitors  Medium Capacity  Fast Charging  Can charge in transfer times  Idle times occurring anyway
  • 23. 23 Christian Henkel © Fraunhofer IPA 2017 Basic Services Aggregated Services Services Integration Services Equipment & CPS VFK Marketplace App1 App2 ... Devices VFK SDK Cloud-based Charging Control Supercapacitor equipped AGVs Cloud Server  Monitoring state of charge  Control of charging stations  Energy Optimization  Intelligent planning of charge times  Integration with production control Smart Objects  AGVs  Charging Stations
  • 24. 24 Christian Henkel © Fraunhofer IPA 2017 Charge-Level-Aware Task Allocation Supercapacitor equipped AGVs Transport Task Manufacturing Station AGV Manufacturing Station with Charging
  • 25. 25 Christian Henkel © Fraunhofer IPA 2017 MRK für körperlich beeinträchtige Menschen
  • 26. 26 Christian Henkel © Fraunhofer IPA 2017 Datenflüsse jetzt WT SensorAktuator Tischhöhe MRK Roboter Warn-/Fehlercodes Schließen/Öffnen WTvorhanden AnzahlDüsen WT Blocker Integrierte Kamera
  • 27. 27 Christian Henkel © Fraunhofer IPA 2017 RFID- Leser Datenflüsse erweitert Kamera Mikrofon Display Bilderfassung Spracherkennung Personenidentifikation Arbeitsanweisungen
  • 28. 28 Christian Henkel © Fraunhofer IPA 2017 Skill-based Assembly
  • 29. 29 Christian Henkel © Fraunhofer IPA 2017 Basic Services Aggregated Services Services Integration Services Equipment & CPS VFK Marketplace App1 App2 ... Devices VFK SDK Intelligente Montage Nieten, Schrauben, Klipsen. Viele Anwendungen. Eine Lösung.  Cloudbasierte Ablage Montageaufgaben  Laden der nötigen Unteraufgaben  Durchführung auf beliebigem Roboter  Programmierung in Cloud  Plattformunabhängig  Zentrale Ablage  Serviceorientierte Geschäftsmodelle
  • 30. 30 Christian Henkel © Fraunhofer IPA 2017 Komponenten  Beliebige Roboter  Integration via MSB  Wartung als Service  ggf. Bereitstellung  PiTask  Verwaltung von Montage-“skills“  Konfiguration  Steuerung Roboter  Monitoring
  • 31. 31 Christian Henkel © Fraunhofer IPA 2017 Time Sensitive Networks
  • 32. 32 Christian Henkel © Fraunhofer IPA 2017 Distributed Robotic Systems Application in Robotics Synchronisation Ethernet Communication TSN Communication Non-Critical Node e.g. Planning Time-Critical Node e.g. Motion Control Internal Clock e.g. ROS Time Non-Critical Node e.g. Task Execution Time-Critical Node e.g. Drive Internal Clock e.g. ROS Time
  • 33. 33 Christian Henkel © Fraunhofer IPA 2017 Use Cases: Control by Wire Time-Sensitive Networking AGV Position Sensor Cooperative Task Omnidirectional Drive
  • 34. 34 Christian Henkel © Fraunhofer IPA 2017 Use Cases: Control by Wire Time-Sensitive Networking Cloud Controller Target Position Disturbance Feedback Positioning Localization
  • 35. 35 Christian Henkel © Fraunhofer IPA 2017 Use Cases: Control by Wire Time-Sensitive Networking Cloud Controller Target Position Disturbance Feedback Positioning Localization = Problems if high Latency
  • 36. 36 Christian Henkel © Fraunhofer IPA 2017 Christian Henkel M.Sc. Project Manager Competence Centre Digital Tools for Manufacturing Tel.: +49 (0) 711 970-1331 christian.henkel@ipa.fraunhofer.de www.ipa.fraunhofer.de Fraunhofer IPA Contact Future is our product Sustainable. Personalized. Smart. Care-O-bot® 4