cooperating robots in manufacturing environmentslms.mech.upatras.gr/lms/files-1/events/02 lms... ·...

Cooperating robots in manufacturing environmentsERF 2015, March 12, 2015, Vienna

Dr. George Michalos (LMS), Dr. Sotiris MAKRIS (LMS)

Aldo Botero (COMAU)

Laboratory for Manufacturing Systems and AutomationDirector: Professor G. Chryssolouris

University of PatrasGreece

Laboratory for Manufacturing Systems and Automation

Director: Professor G. Chryssolouris

General Information

• LMS is involved in a number of research projects funded by the CEU and European industrial partners. Particular emphasis is given to the co-operation with the European industry as well as a number of "hi-tech" firms.

• LMS employs approximately 70 researchers organized in three different groups:

– Manufacturing Processes and Energy Efficiency

– Robots, Automation and Virtual Reality in Manufacturing

– Production Systems Planning, Control and Networking

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Cooperating robots for assembly

•Cooperating robots, are attractive for

• reducing the number of required fixtures

• shortening the process cycle time,

• whilst addressing the accessibility constraints introduced by the use of fixtures

•Their control is based either on the use of

• single controllers, capable of multi-tasking and controlling multiple robots or

• special frameworks, allowing standard controllers to cooperate with each other, by exchanging motion data, as well as synchronization and safety signals.

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Cooperating robots performing spot welding on automotive parts

•An illustrative example

•Two robots

•One is picking up and holding the parts to be welded,

•the second performs the spot welding operation.

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Challenges

• But....

• The control of cooperating robots should be more intelligently accomplished

• ICT infrastructure is required for managing the complexity of cooperation

• Achieving the required tolerances require use of sensors

Serv

ice

(SR

)

Control (C)Local Decisions

Auto adaptation

Networking (N)

Sensing (Sn)

So

ap

Sr CN

SnI/O

So

ap

2h maintenance

needed. Who

can perform the

handling?Estimated arrival

in 15 min.

Sr CSn

NI/O

Sr CSn

NI/O

So

ap

Do not have

suitable tools

Sr CSn

NI/O

Line Level

Reconfiguration

SrCSn

NI/O

Unit Level

Communication

Route part to

next station

Part grasped

securely

5



Scenario of cooperative robots future factory

6

Serv

ice

(SR

)

Control (C)Local Decisions

Auto adaptation

Networking (N)

Sensing (Sn)

So

ap

Sr CN

SnI/O

So

ap

2h maintenance

needed. Who can perform the

handling?Estimated arrival

in 15 min.

Sr CSn

NI/O

Sr CSn

NI/O

So

ap

Do not have

suitable tools

Sr CSn

NI/O

Line Level

Reconfiguration

SrCSn

NI/O

Unit Level

Communication

Route part to

next station

Part grasped

securely

– Automatically generate

assignments of tasks to robots

– Automatically generate

sequencing signals among

robots

– Automatically execute assigned

tasks



AUTORECON – Automotive case

7



AUTORECON – Vision correction

8



9




10




Alternative cooperating robot architectures

• However....

• Alternative cooperating robots architectures are emerging

• Numerous applications can be managed in a more advanced way

• On going research on enhancing user interaction using sensors

11



Service oriented architecture for integration

12



Example

13



AUTOnomous co-operative machines

for highly RECONfigurable assembly

operations of the future

http://www.autorecon.eu

Grant Agreement No: 285189

FoF.NMP.2011-2 “Cooperative machines and

open-architecture control systems”

Acknowledgements

14

http://www.autorecon.eu/



Expert cooperative robots for highly skilled operations for the

factory of the future

http://www.xact-project.eu

Research has received funding from the

European Union's 7th Framework

Programme (FP7/2007-2013) under grant

agreement n°314355

X-act

Acknowledgements

15

http://www.xact-project.eu/



Flexible assembly processes for the Car of the Third

Millennium

http://www.mycar-project.eu

Research has received funding from the

European Union's 6th Framework Programme

under grant agreement n°026631

Acknowledgements

16

http://www.mycar-project.eu/

THANK YOU!

Laboratory for Manufacturing Systems and AutomationDirector: Professor G. Chryssolouris

University of PatrasTel: +30-2610-997262

[email protected]



References

• S. Makris, G. Michalos, G. Chryssolouris, “RFID driven robotic assembly for random mix manufacturing”, Robotics and ComputerIntegrated Manufacturing, Volume 28, Issue 3, June 2012, 359-365.

• S. Makris, G. Michalos and G. Chryssolouris, “Virtual Commissioning of an assembly cell with cooperating robots”, Advances in Decision Sciences, vol. 2012, Article ID 428060, 11 pages, 2012. doi:10.1155/2012/428060.

• G. Michalos, S. Makris, N. Papakostas, D. Mourtzis, G. Chryssolouris, “Automotive assembly technologies review: challenges and outlook for a flexible and adaptive approach”, CIRP Journal of Manufacturing Science and Technology, Volume 2, Issue 2, 2010, Pages 81-91 DOI: 10.1016/j.cirpj.2009.12.001.

• N. Papakostas, G. Michalos, S. Makris, D. Zouzias and G. Chryssolouris, “Industrial Applications with Cooperating Robots for the Flexible Assembly”, International Journal of Computer Integrated Manufacturing, Vol. 24, No. 7, July 2011, 650–660

• G. Michalos, S. Makris, D. Mourtzis, “An intelligent search algorithm based method to derive assembly line design alternatives”,International Journal of Computer Integrated Manufacturing, Volume 25, Issue 3, 2012, 211 -229

• N. Papakostas, D. Mourtzis, G. Michalos, S. Makris, G. Chryssolouris, “An agent-based methodology for manufacturing decision-making: A textile case study”, International Journal of Computer Integrated Manufacturing, , Volume 25, Issue 6, 2012, 509-526.

• S. Makris, G. Pintzos, L. Rentzos, G. Chryssolouris, “Assembly support using AR technology based on automatic sequence generation”, CIRP Annals - Manufacturing Technology, Volume 62, Volume 1, 2013, Pages 9-12.

• D. Mourtzis, N. Papakostas, D. Mavrikios, S. Makris, K. Alexopoulos, “The role of simulation in digital manufacturing – applications and outlook”, International journal of computer integrated manufacturing

• S. Makris, P. Tsarouchi, D. Surdilovic, J. Krueger, “Intuitive Dual arm robot programming for assembly operations”, to appear in CIRP Annals – Manufacturing Technology, Vol. 63, Issue 1, (2014)

• P. Tsarouchi, G. Michalos, S. Makris, G. Chryssolouris, Vision System for Robotic Handling of Randomly Placed Objects, Procedia CIRP, Volume 9, 2013, Pages 61-66.

• G. Michalos, S. Makris, P. Aivaliotis, S. Matthaiakis, A. Sardelis, G. Chryssolouris, Autonomous production systems using open architectures and mobile robotic structures, Procedia CIRP, 2014.

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Cooperating robots challenges

•Coordination, sequencing, collision and communication architectures.

•Real time motion coordination and communication between robot controllers requires higher computational capabilities from the robot controller side as well as protocols for high speed signal exchange.

•The programming aspects of such systems are characterized by higher complexity since programmers need to consider the dynamic nature of real time communication between robots during the generation of code for the control of the robots.

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