28-03-2017 Masterclass Mechatronics 4.0 - Indoor and outdoor localisation and positioning - Localisation of an AGV in a smart factory

Localisation of an AGV in a Smart Factory

131 March 2017© sirris | www.sirris.be | [email protected] |

Filiep Vincent

28/03/2017

Agenda

2

Smart & Digital Factory @ Sirris AGV @ Diepenbeek Artificial reference markers Natural reference points

AGV @ Kortrijk Mobile Industrial Robot

© sirris | www.sirris.be | [email protected] |

Sirris – Collective centre for the Belgian technology industry

3

Mission = To support companies for introducingtechnological innovations

140 people, 8 locations Services to companies

Individual support Share risks Inspiration

Advanced Manufacturing Precision manufacturing Additive manufacturing Smart & Digial Factory


Sirris – Smart & Digital Factory

4

Focus on production systems Smart automation (for small series) Smart assembly Digital operator support Transparent factory

Application labs (D, K, L) Demonstrate technologies/applications: “seeing is believing” Experiment with technologies/applications: “the proof of the

pudding is in the eating” Close collaboration with technology providers


Sirris – Smart & Digital Factory (2)

5

Used technologies Collaborative robots Flexible grippers Digital work instructions Smart glasses (3D) vision systems AGV


Agenda

6




Goal AGV demo

7

To implement an AGV in a CNC production cellfor small series to investigate Challenges for the integrator and end user Potential benefits How to make AGV systems more flexible

Collaboration with Mabo E&A (Lier)


Concept demo

8© sirris | www.sirris.be | [email protected] |

Stations:• CNC-cel• CMM cel• Manual worktable• Warehouse

1 23 4

Implementation


Pallet station for each cell

Implementation

31.03.17 10

Navigation markers + measuring


Implementation

11

Adapt the environment Communication AGV-Master AGV Stations

Cell controller from robotized CNC-machine Cell controller from robotized 3D measuring Manual processing station


Implementation

12

Route creation

Simulation Actual (user screen)



Implementation

Accuracy

14

Go and return between warehouse and CNC


<5mm

Natural reference points

15

We expect: more flexible and less time consuming

Required acc: ±1cm, ±0,5° Teach-in modus needed for

building map


Activities done

16

Survey existing 2D laserscanners Used ROS programs: Pepperl-fuchs_r2000 (driver scanner)

Gmapping (map building)

AMCL (localisation)

Rviz (visualisation)

© sirris | www.sirris.be | [email protected] |Sick, NAV350 Pepperl-Fuchs, OMD30M-R2000-B23-V1V1D-1L

Map buildingGMapping

DriverRS232Odometry

Overview - Map building2D laser scanner ROS program

DriverLaser

scannerMeasurements laser scanner

Map

Ethernet

RS232


AMCL(Adaptive

Monte Carlo Localization)

DriverRS232Odometry

Overview - localisation2D laser scanner ROS program

DriverLaser

scannerMeasurements laserscanner

Map from GMapping

Path-planning Position

Ethernet

RS232

RS232


Hall Mabo NV Changing environment Bad reference points

Floor imperfections

Test in real environment

19© sirris | www.sirris.be | [email protected] |Wall

Tests

Accuracy Natural reference points : ± 5mm Artificial reference markers : ± 15mm

Reliability Context dependant

Cost


Agenda

31 March 2017 22




MiR100

Mobile Industrial Robot Denmark, established in 2013, 1 product Goal = automate in-house transport

Application domains: manufacturing logistics hospitals


MiR100 Hardware 3D camera in front shield: Intel

RealSense 3 m out, ½ meter high after ½

meter Detection from 5-50 cm high

obstacle on the floor

Encoder on 2 differential wheelsused for navigation

Gyroscope used for navigation andorientation

24

Sick laserscanner S300


Controlling the MiR 0) Login: username/passw 1) create map 2) create positions 3) create mission (= program)

positions actions …

4) create operation pattern(s) 5) execute pattern


Planner

Needed: A map (environment) A global plan (navigator) A local dynamic planner (driver)

Motion planning: Based on expanding trees, Search-Based Planning Lab. (www.sbpl.net), Carnegie

Mellon University (US)

Use the lowest cost solution: Distance Cost of each pixel


http://www.sbpl.net/

Application @ lab in Kortrijk 3 cells => 3 positions cell 1 = picking cell cell 2 = assembly cell cell 3 = QC cell

1 mission in infinite loop Push on button = command to proceed Blue LED bar = signals arrival at position


Application SDF lab - map


29

View from MiR


Questions?

31.03.17 30© sirris | www.sirris.be | [email protected] |

31.03.17 31

Thank you for your attention!


+32 491 345 392

[email protected]

Filiep Vincent www.linkedin.com/in/filiepvincent

filiepvincent

31.03.17© sirris | www.sirris.be | [email protected] |

Technology

28-03-2017 Masterclass Mechatronics 4.0 - Indoor and outdoor localisation and positioning - Localisation of an AGV in a smart factory