台灣機器人4.0系統建置 Robot 4.0 System in Taiwan

台灣機器人4.0系統建置
Robot 4.0 System in Taiwan
Jwu‐Sheng Hu (胡竹生), Ph.D
VP and General Director
Mechanical and System Laboratory
Industrial Technology Research Institute
2016/5/30
Copyright 2016 ITRI 工業技術研究院
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Major issues faced by global industries
Rapid market
change
Product life span
decreased
Custom and large-variety
Reshuffle of
manufacture
landscape
small-quantity
manufacture need
Developing country mass
production market
Industrialize country 
custom market
Global
Industrial
Sectors
Slow growth of per capita
GDP
Growth slowed down
after 2008 financial crisis
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Resource and
environmental
issues
Limited global resource
(land, labor, water,
electricity)
Workforce
shortage
Low birth rate
Aging society
Delayed employment
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Key Features of Productivity 4.0
Use intelligent robot to link with
IoT and Big Data technology to
promote manufacturing, service
and agriculture development.
Major Industry
Manufacturing
Service
Agriculture
Application Domain
Mechanical
Equipment
Logistic
Metalworking
Medical
Agriculture
Transport
Tool
3C
Food
Textile
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Promotion of Productivity 4.0
2010
2015
2025
Issues and needs
Current status
Future scenario
Manufacture
Limited productivity of single
robot cell
Multiple robot
collaborated line
Intelligent factory
Flexible logistics
Intelligent logistics
Service
Traditional logistics lack of
flexibility and efficiency
Agriculture
Traditional agriculture
was labor intensive
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Agriculture automation
Intelligent farm factory
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Technology status and trend of Productivity 4.0
2010
Issues and needs
2015
Current status
2025
Future scenario
Intelligent
Robot
Traditional robots
lack intelligence
Hand-eye-force
coordinated robot
Human-robot
collaboration robot
Internet of
Things
Incomplete network and sensing
environment
Consumer product
networking service
Cross industries networking
service
Big Data
Limited data processing
capability
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Cloud data access
Big data service industry
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Intelligent robot for Productivity 4.0
Visualize
Force control
Safe
Hand-eye-force
coordination
Multiple arm
coordination
Human-robot
collaboration
Force control
Human robot
collaboration
Vision guided
3D Vision
Multi-robot
coordination
Major International robot vendor
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Human-robot safety
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Robot 4.0 Needs
• Adapt to small‐quantity large‐variety manufacturing
– Robot needs to generate motion automatically for environmental and task changes
– Robot + IoT for preventive maintenance – Human robot collaboration to maximize flexibility and efficiency
– Robot needs to be safe to human co‐workers
– Robot needs higher precision to guarantee cyber‐physical consistency
– Robot needs natural user interface (NUI)
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Robot 4.0 Technology
• Machine intelligence: – Human develops decision logics  Machine learns decision logics
– Task assignment by programming only  Multi‐modal task assignment
• Application development:
– Trial‐and‐error  Digital virtual prototyping
• Vision: – 2D Vision (RGB)  3D Vision (RGBD)
• Tactile sensing: – Joint force/torque  Contact sensation
• Spatial‐temporal perception
– Working at fixed environment  Working at changing environment
• Human‐robot safety:
– Fence isolation  Human robot next to each other
• Prognosis: – Fix a problem when it happens  Prepare for the problem before it happens
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Status of Taiwan industrial robot
• Taiwan industrial robot industry is taking shape
•
•
•
•
Robot: Foxconn, Hiwin, Everrobot, Foxlink, Tech Man, Toptek, etc.
Controller: Syntec, Advantech‐LNC, Nexcom, Motorcon, etc.
Servo motor & driver: Shilin Electric, Delta, Hiwinmikro, Teco, etc.
Transmission Mechanism: Hiwin, Apex Dyanmics, TPI Bearings, etc.
• ITRI’s effort to create and support the industry
• More than 50,000 robot controllers shipped
• Tech transferred robotic technologies to Hiwin, Foxlink, Tech Man, Toptek, Nexcom, etc.
• Supported Everrobot, Tailift, Shilin Electric, Teco, etc. on robot and controller development
Tech
Transfer
6-axis A-type SCARA
Robot Controller
Foxlink
Hiwin
Toptek
Tech Man
Nexcom
Tech
Support
6-axis A-type
Robot Controller
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Foxcon
Everrobot
Shilin Electric
Teco
Tailift
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From R&D to Industrial Practice
Users (manufacturing)
Component
Makers
Equipment Makers
Robot
Makers
Software
Developers
University and Institutional Research
Research Subsidies
System Integrators
Government and Private Funding
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Highlight of ITRI Robotics Technology
CPS & Safety
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ITRI MIO Robot Controller
Intelligence
Orchestration
•Easy to use
•Intelligent sensing
•Safety detection
1
1.
2.
3.
4.




Robot CAD/CAM module
•Coordination
•Network
•Value‐added software MIO robot controller‐Basic
Position Data
Position Data
500
500
S100 (mm/s)
S500 (mm/s)
S1000 (mm/s)
RCL motion library
Singularity protection
Collision avoidance
True motion planning
F500P20
F500P100
F500P200
450
450
Y (mm)
•Fast、Stable and Accurate
•Accuracy upgrade
•Optimal motion planning
Y (mm)
Motion 400
350
-50
400
0
50
X (mm)
100
350
-50
0
50
100
X (mm)
 Auto processing-path generation, Robot
motion, Singularity detection
Robot accuracy improvement module
Vision-based Hand-eye coordination
module
Tactile-based safety module
4
MIO robot controller‐
Extended module
Motion Intelligence Orchestration
3




2
MIO robot controller‐Advance



Contain MIO controller-Basic type
Support velocity and torque control
Provide sensorless compliance teaching
(lead-through)
eMIO robot controller‐Network type
Support EtherCAT control; International standard
protocol
Contain MIO controller-Basic and -Advance type
function
Real time digital communication and serial
networking structure, flexible electric wiring,
Support industry 4.0 IoT and self-diagnosis function
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ITRI工業技術研究院
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ITRI Production Line Simulator
• Key Features:
―
―
―
―
―
―
Multi‐physics simulation including sensors
Hardware‐in‐loop (HIL) simulation capability
Supports algorithm development and testing 3D factory layout, throughput analysis, optimization, and scripting
Model database with various robot and equipment models
Virtual space to real space direction connection
▲Virtual controller integrating virtual and real component
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▲Robot arm, virtual sensor, and conveyor models
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ITRI Precision Robotics Technology
Static Precision
Link
Real
Virtual
Position Data
500
Y (mm)
Dynamic
Precision
6 dimensional
path tracking
Ideals space
450
Distorted space
400
350
-50
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0
X (mm)
50
100
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ITRI 3D Robotic Vision
RGBD Camera using Diffractive Optical Element
‐ Resolution : 1280x960 ‐ Distance: 80 ± 15cm
‐ Accuracy: ~0.5mm ‐ Frame rate: 30 fps
Virtual Space Simulation
Statistical Learning for object pose estimation
‐ Object simulation under physic engine ‐ Scene management and virtual sensor
Real Image
Speckle Image
Depth Image
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CPS for Random Bin Picking (Cyberspace)
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CPS for Random Bin Picking (Real space)
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CPS for Robot Grinding/Polishing System
• Absolute accuracy of robot trajectory to support simulation (CPS)
• Trajectory generation/verification in cyberspace and robot command generation
• Sensor fusion and control for polishing path correction considering workpiece deformation and variation in contact force (e.g., belt tension)
Traditional process
Material
Foundry
Manual coarse polishing
Forging
Manual fine polishing
CPS‐Robot Polishing Structure
ITRI EzSim
Offline programing
Deformation
measurement
Model‐based CPS
Cloud server
Deformation
data
Path correction
Accuracy
Information
Prediction
Polishing pathDiagnosis Control
Control
ITRI robot controller
Smart belt
Intelligent robot
Accuracy deviation sensing
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Belt tension
Force sensing
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Safety requirements for collaborative robot
ISO/TS 15066
1. Speed and separation monitoring
Robot can slow down when operator enters the work space
2. Safety‐rated monitored stop Robot should be stopped when operator touch the robot.
3. Hand Guiding
Robot motion only through direct input of operator
4. Power and force limiting
In contact events, robot can only impart limited static and dynamics forces
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ITRI Safety Robot
•
Satisfy safety requirements of collaborative robot
– ISO/TS 15066 (Standard in development )
•
Collision sensing skin
AR602s
– Sensor thickness < 0.3 mm
– Density < 10 mm – Flexible cover containing high density sensor (3000 nuts)
– Robust to environmental disturbance
•
EtherCAT‐based eMIO controller
– Sensorless compliance teaching
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Conclusion
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3 Dimensional Challenge and Opportunity
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Intelligent Manufacturing
• Equipment investment vs knowledge investment
–
–
–
–
Turn knowledge into key device
Turn knowledge into high‐value equipment
Turn knowledge into advantageous business model
Turn knowledge into core competence
• Use of ICT technology to achieve continuous improvement
– Any detail information from stocking, manufacturing, shipments, to customer feedbacks can help improve productivity
• Make use of ICT technology to reinforce the strength of industrial clusters for machinery and manufacturing
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