alborg Universitet, Denmark
–
–
–
–
role: R&D, technology transfer
mission instruction, planning and control
industrial manipulation
visual perception for quality control
lberts-Ludwig Universität, Germany
– role: R&D, technology transfer
– life-long navigation
– precise local navigation and fast docking
WWW.STAMINA-ROBOT.EU
LR, Germany
Sustainable and reliable robotics for part handling in manufacturing automation
– role: R&D, technology transfer
– 3D modelling and object/obstacle recognition
– manipulation: picking and placing of load carriers and parts
TAPAS Proposal – 3 November 2009
27
OVERVIEW
WHY? Motivation of the Proposal!
• WHAT? Objectives of the Proposal!
• HOW? Activities!
• WHO? Partners!
• Conclusions
•
WHY?
Motivation of the Proposal
• STAMINA : building the Factory of the Future with the help of new robotics
technologies!
• Find profitable solutions to increase the competitiveness of EU!
• Increase the flexibility of production facilities to face:!
• Ever increasing customisation of products!
• Production volumes variations!
• Address ageing workforce issues and occupational diseases!
• Allow the deployment of workers to tasks of greater interest and value added for
the customer
Synchronization of referenced parts
Transfer parts to the production line
Kitting operations
Transfer parts to the production
The challenge
•Unload heavy parts from a bulk-storage or palette !
•Feed the isolated part in the proper position and
orientation!
•7 seconds / part
The benefits
•Ergonomics : 4000 parts / shift (up to 20 tons)!
•Cost-effective : 75% of the price of
installations on feeders!
•Deployment : 215 applications with bulkstored parts identified
Synchronization of referenced parts
The challenge
•Reorder parts according to production request!
•Fragile parts (7kg) can only be grasped by specific
zones!
•9 different parts in different storage conditions!
•3 min to prepare 20 parts
The benefits
•Ergonomics : 12 tons / shift!
•Quality (conformity, traceability)!
•Deployment : every plant
Kitting operations
Definition : Process in which individually separate
but related items are grouped, packaged, and
supplied together to the production line
The challenge
•Gather a selection of parts and place it on a carrier!
•Diversity of parts (shape, flexibility, colour)!
•Different storage conditions in a wide area!
The benefits
•60 sec to prepare a full kit
•Flexibility to production changes!
•Quality (traceability)!
•Deployment : 99% of vehicle parts are
delivered in kits (goal)
TECHNOLOGICAL CHALLENGES
Bin picking, de-palletising, kitting and part feeding!
• Object recognition and Grasping capabilities!
• Safe navigation among humans!
• Cooperation with fleet of mobile robots and/or manual forklifts!
• Control through the ERP System!
• Easy programmable by humans!
• Compliance with safety regulations
•
TECHNOLOGICAL CHALLENGES
!
•
Sustainability: !
• easy adaptability to new tasks and missions!
• able to automatically compensate for limited variability !
• programmable even by shop-floor workers!
• Complies with safety requirements as far as possible
WHAT?
Objectives of the Proposal
Solve the above three use-cases with a mobile robot such that
the robot has the following set if skills
!
1.able to navigate safely!
2.able to bin-pick within the given use-cases!
3.able to place parts + inspect part!
4.able to communicate with other robots!
5.do all this in a safe way
The Solutions are Reliable and Sustainable
!
1.works in all three use-cases!
2.only minor re-programming efforts!
3.with parameters provided by human / MES system
Advanced Human Robot Interface
!
1.normal shop-floor workers!
2.MES system of the company can interface with the robot!
3.safety requirements are assured by the HRI
The System Complies as much as Possible with the Safety
Requirements
!
1.Proactive work on safety measures by choosing right HW, sensors!
2.Provide input to revision of industrial requirements for use of
mobile, cooperative robots!
3.Risk analysis across all test-sprints
HOW?
1. AVAILABLE ROBOT TYPES
Robm@rket, based on Artemis AGV, BA-Systémes!
• ROBY, BA-Systémes!
• Little Helper Robot, AAU --> Skill concept, HRI
•
2. LEAN DEVELOPMENT
R&D
3
3
Validation
Implementation
Testing at End-user Site
2
0
2
4
1
3
2
4
1
2
4
1
1
5
Knowledge Transfer
M10
M21
M31
M41
M42
Regular test-sprints will assure constant !
• focus, !
• fast identification of safety issues and fast accommodation of user feedback!
• Tests under realistic conditions!
• direct technical feedback
•
Review, Feedback
University/Lab
Integration&Developmet
UBO - Bin Picking!
•
• ALU-FR - Navigation!
• INESC - Fleet-control!
UEDIN - Planning!
•
•AAU - Skills, HRI, part-feeding,
•
•
•
inspection!
!
Provide code that !
is state-of-art!
runs under lab conditions!
works on the use-case
objects
•
BAS - Integration!
!
Provide !
• prepare code to run under
use-case conditions!
• prepare the hardware for usecase conditions.!
• documentation, quality control!
safety !
•
testing
•
Review, Feedback
Shop Floor
•
PSA - Experiments!
!
Provide !
use-case scenario!
•
• optimize code under use-case
conditions!
• optimize hardware for usecase conditions.!
• documentation, quality control!
safety !
•
testing!
•
user-testing
•
Review, Feedback
WP1: Integration, testing, Use case-definition, validation and evaluation!
!
T1.1
T1.2
T1.3
T1.4
Direct implementation
only for the M10
experiments
WP2: Robot Control
!
T2.1
Feedback from the
experiments
T2.2
T2.3
T2.4
T2.5
Skill Concept, & Architecture
WP3: Skills for differentiated robot fleets
T3.1
T3.2
T3.3
T3.4
WP4: Mission tasks and vertical enterprise integration
T4.1
T4.2
T3.3
T4.4
•
•
•
Implementation input: !
Code works in lab space!
on parts!
embedded in skills
WP1
INTEGRATION, TESTING, USE CASE-DEFINITION, VALIDATION AND EVALUATION
definition of the targeted use-cases !
• hardware requirements!
• define user requirements and performance and usability criteria !
• allow incremental integration of hardware and software designed in WP2-4 !
• conduct iterative test cycles for evaluation and feedback to R&D partners!
• assure safety proactively where possible, and derive new solutions where necessary,
together with WP2-4!
• carry out a safety risk assessment with associated risk reduction measures
•
WP2: ROBOT CONTROL
Provides the “low-level” capabilities of the STAMINA-Robot!
• Localization and Mapping!
• Robot Navigation!
• Picking!
• Single Part Feeding and Inspection!
• Inter-robot coordination and communication!
• Safety criteria are provided by WP1 and are considered within each sub-task.!
!
Success-criteria: Provided code runs under lab-simulated use-cases settings while taking into
account the requirements provided by WP1.!
-ICT-2013-10
7/2012 v1
STREP proposal
STAMINA
WP3: SKILLS FOR DIFFERENTIATED ROBOT FLEETS
h skill is defined by a Precondition check, by a Prediction, and by an Evaluation (see Figure 7). The
cution contains the robot control (motion primitives)
On
the
robot: check is meant to assert the
m WP2.
The
precondition
essful
execution
a robot
control (WP2).
E.g. forof robot
• defines
“skillofAPI”
to supports
integration
ing, the
object from
must WP2!
be reachable. If the precondition
controls
k evaluates to true, the skill may be executed. After
•
the set checks
of necessary
skills
required e.g.,
to
ution,identify
the evaluation
if all was
successful,
complete
common
e object
is in thethe
gripper
of the missions!
robot. Precondition
WP 2 code
k and
evaluation
evaluate
vector,robot
whichcontrols
is
• actually
integrate
thestate
different
from
posedWP2
of task
state
world-state
into
theinformation,
skill structure!
rmation
and robot state information. Sensory devices
• implement task-planner that controls skills!
used to compute the state vector.
Figure 7 depicts a skill [Bøgh et al.2012]. It
• define HRI based on touch pad and possibly othercontains the Preconditions that assert correct
example,
imagining the kitting use-case 2.3: the robot
execution given the present task state, the
modalities
is to fill
the kit with different parts that need to be
Evaluation evaluates if the skill execution was
hed from different pallets. For picking a part, the robot
successful, the function block for the physical
Execution, and the Prediction is given by the
o be close enough before the pick-skill can be
expected outcome. The gray parts are necessary
uted. If the robot is not close enough the navigation
for planning.
has to be executed to bring the robot closer to the
Which skill to execute is ideally up to the decision of
WP4: MISSION PLANNER AND VERTICAL ENTERPRISE INTEGRATION
Mission Planner
Skills
Robot
Task Planner
Enterprise
Not on the robot:
• specify API between MES system and mission-planning
subsystem!
• integration mechanisms with MES systems!
• provide the software level integration to support
communication between MES and mission planner!
• define and implement the mission planning subsystem
MES
WP5: KNOWLEDGE TRANSFER, DISSEMINATION AND EXPLOITATION
•
Academic Partner:
• public dissemination!
• conferences, workshops!
• fairs!
• journal publications!
!
•
Industrial Partners:
• exhibitions, fairs (Automatica, Hannover industrual fair, etc)!
• shop-floor of PSA show-case to partners (e.g. EADS) and suppliers (manufacturing and product parts)!
!
use of the stamina robot at the PSA plants!
• BAS: building and selling advanced AGVs
•
WHO?
Partners and Roles
Aalborg University, Denmark (Coordinator)
coordinator, project administration, research!
•part-feeding and inspection!
•robot skills concept
PSA Peugeot Citröen, France:
system integrator, end-user!
•application development!
•testing and validation!
•use-case definition, definition of benchmarks, !
•safety
BA Systémes, France:
technology provider, system integrator !
•robot and application development, safety; !
•testing and validation!
•safety
– mission instruction, planning and control
– industrial manipulation
– visual perception for quality control
University
of Freiburg,Universität,
Germany Germany
• Alberts-Ludwig
•mapping!– role: R&D, technology transfer
•localization!
– life-long
navigation
in dynamic
environments
•robust navigation
– precise local navigation and fast docking
University
Bonn, Germany
• DLR,ofGermany
•Bin-picking
– role: R&D, technology transfer
– 3D modelling and object/obstacle recognition
INESC-Porto,
Portugal
– manipulation:
picking
and placing
of load
coordination and
cooperative
mapping,
! carriers and parts
•multi robot
•ERP integration, Network interfaces
TAPAS Proposal – 3 November 2009
University of Edinburgh, UK
•task planning, execution monitoring of robot task plans, !
•fleet-level/mission planning
27
CONCLUSIONS
•
Key objective
• build a robot system that is equipped with capabilities to handle a set of logistic
tasks while assuring that the system is sustainable:!
• it is NOT overspecialised!
• it is easily adaptable to new scenarios !
!
•
3 use-cases are used to achieve that:
•
kitting
•
bin-picking
•
de-palletizing