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AMC HOFMANNPO BOX 115664629 HEPPENHEIM, GETELEPHONEEMAIL: HOFMANN@AMCWEB: WWW.AMC
Market Report Bin PTECHNOLOGIES
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ickingINDUSTRIES
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Market Report Bin Picking
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TABLE OF CONTENTS
1 Introduction ......................................................................................................................................... 7
What is so difficult with bin picking? ............................................................................................................. 7
Goals of the market report ............................................................................................................................ 8
Summary of the market Report .................................................................................................................... 8
Generation of data - Research ..................................................................................................................... 9
Definition of used terms .............................................................................................................................. 10
2 Market Report Summary .................................................................................................................. 11
Automation Technology opens up Bin picking solutions ............................................................................. 11
Common understanding of bin picking ....................................................................................................... 11
Focus on solutions ..................................................................................................................................... 12
End user survey ......................................................................................................................................... 12
Successful Solutions .................................................................................................................................. 13
Solutions with additional mechanical part separation .............................................................................................. 13
Standardizing bin picking technology ...................................................................................................................... 14
Solution Concepts ...................................................................................................................................... 15
Description Stationary Concept ............................................................................................................................... 15
Technologies .............................................................................................................................................. 16
Detection Technologies ........................................................................................................................................... 16
Vision Algorithms ..................................................................................................................................................... 17
Handling, Robotics and Gripping ............................................................................................................................. 18
Market Overview ........................................................................................................................................ 19
Vendor Overview ........................................................................................................................................ 20
3 Market needs ..................................................................................................................................... 21
End- User survey ........................................................................................................................................ 21
Introduction .............................................................................................................................................................. 21
Meeting technical criteria and budget needs ........................................................................................................... 21
Maintenance ............................................................................................................................................................ 22
Parameterization of a cell for new parts .................................................................................................................. 22
MMI – MAn Machine Interface ................................................................................................................................. 22
Responsibility and Competence .............................................................................................................................. 23
Market Report Bin Picking
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4 Technologies .................................................................................................................................... 24
Introduction ................................................................................................................................................ 24
Basic concepts for system set-up: .............................................................................................................. 24
Algorithms .................................................................................................................................................. 25
Basic Machine Vision tools ...................................................................................................................................... 25
Correlation based tools ............................................................................................................................................ 25
Point Cloud analysis ................................................................................................................................................ 26
Detection Technologies .............................................................................................................................. 27
3D- Detection Technologies ....................................................................................................................... 28
3D (Laser-) Triangulation ......................................................................................................................................... 28
Photogrammetry ...................................................................................................................................................... 30
Photogrammetry- 3D with one camera .................................................................................................................... 31
Stereometry ............................................................................................................................................................. 32
3D Laser Scanning .................................................................................................................................................. 33
3D ToF (Time of Flight) ........................................................................................................................................... 35
Gripping ...................................................................................................................................................... 36
Robots & Handling ..................................................................................................................................... 37
Robot path planning ................................................................................................................................... 37
5 Turnkey- Concepts ........................................................................................................................... 38
Introduction ................................................................................................................................................ 38
Back- up Strategies .................................................................................................................................... 38
Cell Concepts ............................................................................................................................................. 39
Stationary Concept .................................................................................................................................................. 40
Robot mounted ........................................................................................................................................................ 41
Hybrid ...................................................................................................................................................................... 42
Additional stationary Detection Unit......................................................................................................................... 43
Additional station ..................................................................................................................................................... 44
Additional mechanical Part separation .................................................................................................................... 45
Market Report Bin Picking
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6 Market Overview ............................................................................................................................... 46
Introduction ................................................................................................................................................ 46
Automotive Overview ................................................................................................................................. 47
Automotive – Body in White / Press shop .................................................................................................. 48
Overview, General description ................................................................................................................................ 48
Application Example: Unloading of pressed parts and De-Racking ........................................................................ 48
Automotive – Powertrain ............................................................................................................................ 49
Overview, General description ................................................................................................................................ 49
Application Example: Break Disk Handling ............................................................................................................. 50
Automotive – Tier 0.5 & Tier 1 .................................................................................................................... 51
Overview, General description ................................................................................................................................ 51
Application Example: Unloading of Gear Shafts ..................................................................................................... 52
Aerospace .................................................................................................................................................. 53
Overview, General description ................................................................................................................................ 53
Food & Packaging ...................................................................................................................................... 54
Overview, General description ................................................................................................................................ 54
Application Example: Picking of Food ..................................................................................................................... 54
Application Example: Picking of Packaged Food .................................................................................................... 54
Logistics ..................................................................................................................................................... 55
Overview, General description ................................................................................................................................ 55
Application Example: Warehouse Automation ........................................................................................................ 55
Application Example: Distribution Center – The Parcel Robot ................................................................................ 56
Pharmaceuticals - Overview ....................................................................................................................... 58
Overview, General description ................................................................................................................................ 58
Application Example: customizing daily packages .................................................................................................. 58
Bin picking related applications .................................................................................................................. 59
Overview, General description ................................................................................................................................ 59
Application Example: Picking of Bins ...................................................................................................................... 59
Application Example: De-Palettizing of sacked/Bagged goods ............................................................................... 60
How to find bin picking applications ............................................................................................................ 61
7 Supplier Overview ............................................................................................................................ 62
The Survey ................................................................................................................................................. 62
Vendors by Core Competence ................................................................................................................... 62
Chart - Core Competences of the vendors .............................................................................................................. 62
Core Competence - Key figures .............................................................................................................................. 63
Chart - Core Competences of System Integration Vendors .................................................................................... 63
Table, Core Competence ........................................................................................................................................ 64
Vendors by Business Activities .................................................................................................................. 65
Business Activities - Key figures .............................................................................................................................. 65
Chart - Robot & Automation Companies Supply of Machine Vision ........................................................................ 66
Chart, Machine Vision Companies Supply of Automation ....................................................................................... 66
Table, business fields .............................................................................................................................................. 67
Market Report Bin Picking
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Vendors by Business Region ..................................................................................................................... 68
Table, Vendor, Business Region ............................................................................................................................ 68
Vendors by Industries ................................................................................................................................. 70
Industries Overview - Key figures ............................................................................................................................ 71
Chart- Industries where Vendors are active ............................................................................................................ 71
Chart - Industry Distribution by Core Competence .................................................................................................. 71
Table, Industries where vendors are active ............................................................................................................. 72
Vendors by Industry - Automotive details ................................................................................................... 73
Chart - Automotive detailed Overview ..................................................................................................................... 73
Automotive detailed Overview - Key figures ............................................................................................................ 73
Table, Automotive detailed ...................................................................................................................................... 74
Vendors by Handling Systems Supported / supplied .................................................................................. 75
Handling Systems supplied and / or supported Key Figures ................................................................................... 75
Chart - Handling Systems Supplied and / or supported .......................................................................................... 75
Table, Handling Systems supplied / supported ....................................................................................................... 76
Vendors by Vision Systems & Sensors ...................................................................................................... 77
Chart - Vision used and / or supported .................................................................................................................... 77
Vision Systems & Components Key Figures ........................................................................................................... 78
Table - Vision Systems Components ...................................................................................................................... 78
Vendors by Detection Technologies ........................................................................................................... 79
Detection Technologies Key Figures ....................................................................................................................... 79
Chart- Detection Technologies used, supported or provided .................................................................................. 79
Chart- Comparison, Detection Technologies used in Automation and Machine Vison ........................................... 80
Table - Overview Detection Technologies ............................................................................................................... 81
Vendors by Algorithms used or supported ................................................................................................. 82
Detection Algorithms Key Figures ........................................................................................................................... 82
Chart- Algorithms available ..................................................................................................................................... 82
Table, Algorithms ..................................................................................................................................................... 83
Vendors by Gripping Technology used or supported ................................................................................. 84
Gripping Technologies Key Figures ........................................................................................................................ 84
Chart - Gripping Technologies................................................................................................................................. 84
Table, Grippers ........................................................................................................................................................ 85
Vendors by TurnKey Concepts................................................................................................................... 86
Cell Concepts Key Figures ...................................................................................................................................... 86
Chart, Support of Cell Concepts .............................................................................................................................. 86
Table, Cell Concepts ............................................................................................................................................... 87
Overview Installed Systems & Prototypes .................................................................................................. 88
Installed Systems and Prototypes Key Figures ....................................................................................................... 88
Market Report Bin Picking
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Appendix A, Publications .............................................................................................................. 89
Advenovation: Manufacturing Operation .................................................................................................... 89
PointGrey and Cognex to unveil real-time 3D part alignment ..................................................................... 92
DHL discover logistics: The comeback of the robots .................................................................................. 93
Fanuc Robotics: Robots Use 3D Vision to Improve System Costs and Product Quality ............................ 96
Fanuc Robotics: Fanuc Demonstrates Intelligent bin picking at IMTS 2006 ............................................... 99
Fraunhofer, IPA- bin picking ..................................................................................................................... 101
Isra Vision: bin picking with a 3D Sensor ................................................................................................. 103
Isra Vision: MONO3D Vision System Automates DaimlerChrysler Body Shop Operations ...................... 105
Mafu: bin picking ...................................................................................................................................... 107
Profactor: iRobFeeder .............................................................................................................................. 108
Scape Technologies: Disc Bin- Picking and Loading ............................................................................... 110
Thyssen Krupp Krause: A helping hand from parcel robot ....................................................................... 111
Tordivel: New 3D bin picking Concept in R&D Project Autocast .............................................................. 113
VMT: Modular, Efficient, Versatile – Platform Strategy for Automated Material Handling ........................ 114
Appendix B, Vendor Listing in alphabetical order ......................................................................... 117
Appendix C, SOURCES ..................................................................................................................... 123
Sources for additional internet-based research ........................................................................................ 123
Copyright .................................................................................................................................................. 125
Market Report Bin Picking
©AMC Hofmann Automation – Market – Competence Page - 7 -
1 INTRODUCTION
WHAT IS SO DIFFICULT WITH BIN PICKING?
Nothing!
Bin picking simply means that a box or bin has to be automatically unloaded.
Typically by using a robot with a gripper and a vision system.
Everything!
There are many different industries that have a need for bin picking. Due to the parts and conditions bin picking can be either a
simple task or a very difficult application.
The range of complexity is very large
The range of products to be picked is similarly large
The tools / solutions to solve the task are extensive
Different handling systems
Different gripping technologies
Different grippers
Different detection technologies
Different detection algorithms
Different system set-ups (cell concepts)
Talking to companies, either suppliers or users of automation about bin pickingcan result in many different answers and conclusions about feasibility. This ismainly depending on their experiences from the past and their personalunderstanding of the application as well as their core competence and theindustries where they are active.
And all of them are right or wrong depending on the specifics of the applicationcoupled with the customer´s expectation
Without much detailed information about the parts to be picked and all process and site conditions a serious statement about
feasibility is not possible.
Different industries do have different needs and process conditions
Different parts require different grippers
Different parts require different detection technologies
Different boxes & bins influence the process
Market Report Bin Picking
©AMC Hofmann Automation – Market – Competence Page - 8 -
GOALS OF THE MARKET REPORT
There are several goals of this report. It depends on your business and your responsibilities which of them to value the most.
Goals of the report
Provide a better understanding about the “myth” bin picking
Provide a deeper understanding on the available technologies and products
Provide an overview on available solutions and concepts
Provide a closer look at customer requirements and site conditions
Provide overviews on new potential business opportunities (applications & industries)
Provide an outlook to the near future opportunities for bin picking
Provide information and contact data on vendors and suppliers
SUMMARY OF THE MARKET REPORT
Industrial Automation – Market Report Bin Picking
Bin picking is one of the applications in industrial automation still offering great potential for efficiency increase inproduction and material handling in many industries
Especially in difficult market situations, like the one we are experiencing since the beginning of the financial crisis,
manufacturers of goods as well as the whole automation market are looking for new or additional possibilities to open up
efficiency and cost reduction potentials by introducing process automation. This might be one of the reasons for the recently
increased interest in the application of “bin picking”, the automated unloading of unsorted parts from transport boxes.
Now, a comprehensive market report on this topic is available for the first time ever. By interviewing both, suppliers and users in
many different industries, such as Aerospace, Automotive, Food & Packaging, Foundry, Logistics, Medical Engineering, and
Pharmaceuticals the compilation of an extensive survey of the market was achieved. The market report “bin picking” provides an
in-depth insight into customer requirements, technologies, products, and turnkey solutions. The report presents information
about turnkey suppliers, system integrators and product and component manufacturers out of Europe and North America.
The report includes information about the automation industry and technology leading companies such as, e.g., ABB Robotics,
Adept Technology, Cognex, Denso Robotics, Inos Automation, PPT Vision, Sick IVP, Motoman Robotics, MVTec and Tordivel.
Over 40 companies focused on bin picking and related applications are covered by the report.
Data comprised in the report has been mainly generated by direct interviews conducted with the leaders in this field of
automation. In order to have a very comprehensive overview the results of additional research with a variety of sources such as
internet, trade shows, presentations, publications and conferences have been included in order to complete a very thorough
overview.
Market Report Bin Picking
©AMC Hofmann Automation – Market – Competence Page - 9 -
GENERATION OF DATA - RESEARCH
Data used: All used information is either public or provided and submitted by the companies included in the survey.
Therefore the correctness of the information oblige to these sources.
Data handling and analysis within the tables and charts:
X Topic is represented by the company
P Topic is represented by partners
--- Company does not provide the topic
No information was submitted on this topic
Due to the fact that not always information or statements have been submitted bythe companies, adding the numbers in the charts does not necessarily add up to100%
Note
In order to give a broad and complete overview information provided in this report
are not limited to the information of the questionnaires. Material available in form of
presentations or out of websites is added as well. All sources been used are listed
in the appendix.
Methods: Data generation of information was done by the following methods
Web research
Literature research
Direct personal communication to vendors and users
Questionnaires sent out to vendors
Questionnaires sent out to users
Geography: In order to get an international overview, companies in the following regions have been involved in this survey:
Europe
North America
Australia & New Zealand
Confidentiality: All information / data published in this report has either been confirmed and publicly released by the
providing companies to be published in this report or derived from public sources.
Market Report Bin Picking
©AMC Hofmann Automation – Market – Competence Page - 10 -
Industries: In order to get a complete view on possible applications the following industries, with known interest in bin
picking, have been directly involved:
Aerospace
Automotive (BIW & Press shop)
Automotive (Assembly)
Automotive (Logistics)
Automotive (Powertrain)
Food & Packaging
Foundry
Logistics
Medical Engineering
Pharmaceuticals
Recycling
Tier 0.5 & Tier 1
By interviewing automation integrators and automation product manufacturers’ needs and potentials of other industries are
indirectly covered as well. The report provides these information as far as the companies have approved / released them.
In order to get a clear and better understanding of the numbers shown in the report provided by the companies it needs to be
pointed out that some differ from industry to industry. So for example an application of handling cast parts for automotive can be
counted under Foundry, Logistics, T0.5 & T1, or Automotive, depending on the vendor´s definition.
In the same way end-users are organized differently; one manufacturer may be running their own foundry, a competitor is
buying the parts from a supplier.
DEFINITION OF USED TERMS
Many times terms are used in different ways. To avoid misunderstanding please read the following definitions.
Detection unit- For this report “detection unit” is defined as the unit generating image information. The detection unit can
consist of a full set- up of illumination and optics, combined with a single sensor, several sensors or a set-up of a scanner and
single cameras.
OEM- official definition is „original equipment manufacturer“. However, car manufacturers refer also to themselves as OEM. In
this report the term OEM is used to describe automation equipment manufacturers, including machine builders, with a high
degree of standardization. A robot manufacturer for example would be an OEM.
Sensor- is generically used in this report to describe the various kinds of optical units integrated within one housing. This
includes the entire range from simple standard sensors to stereo-optic and triangulation sensors.
T0.5 & T1- Tier 0.5 & Tier 1 are terms specifying key automotive suppliers, classified into 0.5, 1 and 2 depending on their scope
of delivery and the extent of involvement in the processes and in the research and development done by the car manufacturers.
Powertrain- Powertrain is the naming for automotive manufacturing and parts that are used in underbody frame and engine and
transmission manufacturing. Powertrain includes the car manufacturers´ facilities as well as the Tier Supplier.
Random bin picking- Random bin picking many times is used instead of bin picking to indicate that the goods in a bin are
without any known or defined orientation.
Market Report Bin Picking
©AMC Hofmann Automation – Market – Competence Page - 11 -
2 MARKET REPORT SUMMARY
AUTOMATION TECHNOLOGY OPENS UP BIN PICKING SOLUTIONS
Especially in difficult market situations, like the one we are experiencing since the beginning of the financial crisis,
manufacturers of goods as well as the whole automation market are looking for new or additional possibilities to open up
efficiency and cost reduction potentials by introducing process automation.
This might be one of the reasons for the recently increased interest in the application of bin picking. By interviewing both,
suppliers and end-users in many different industries, the compilation of an extensive survey of the market was made possible in
this report. At the same time, the report advances a common understanding for bin picking applications by information and know
how transfer. The market report “Bin Picking” provides an in-depth insight into customer requirements, technologies, products,
turnkey solutions, and suppliers.
COMMON UNDERSTANDING OF BIN PICKING
With the term “bin picking” most users associate the unloading of parts of random orientation out of a bin by gripping them part
by part with a robot. Several scenarios can emerge which make it impossible to get all parts out of the box without additional
tools or strategies:
a part cannot be recognized (detected),
a robot path to grip a part cannot be created (caused, e.g., by the bin
itself presenting an obstacle for approaching the part),
a part cannot be gripped, because the gripping point is obstructed,
a part cannot be taken out of the box because it is jammed with other
parts.
Successful “bin picking”, without additional mechanics or
part separation, requires all of these steps being
successful: part detection, gripping, generation of the
robot path, unloading.
Advenovation, typical random bin picking scenario.
So, what is necessary to solve more industrial “bin picking” applicationssuccessfully?
Market Report Bin Picking
©AMC Hofmann Automation – Market – Competence Page - 12 -
FOCUS ON SOLUTIONS
The common goal of users and suppliers of automation technology is always a working, cost efficient solution with high
reliability. To meet this goal it is necessary to develop a common understanding of the real application requirements, the
technologies being used, and the potential challenges coming with the application and the respective options for solutions. The
expectation that it is possible to simply mount a camera on top of a box and have it transfer the position coordinates of randomly
orientated parts to a robot which then picks all parts without any additional tools will never be met.
Discussing about the application should mean thinking of the total solution rather then what components are to be used. There
is no isolated view on robot, gripper or machine vision system. Each subsystem is capable of many things in general, but there
needs to be a working solution consisting of all these subsystems cooperating. If the vision system detects a part, but the
gripper cannot pick the part the application won´t work. And if there are parts left in the box that could be picked, but not being
detected by the vision system, it will not work either. Deep understanding of the application and the subsystems used enable
integrators to come up with the best solution possible.
END USER SURVEY
It seems to be the normal evolution of automation applications that as soon as an application is solved, companies are pushing
their suppliers to standardize and simplify.
Therefore it is important to keep the most important topics of manufacturing companies always in mind. Manufacturing
equipment needs to help produce parts. Success always depends on the following criteria that have been pointed out by the
end-user interviewed as most important:
Investment needs to pay off, based on current conditions in a company
Solutions need to be reliable and meet customer specifications
Maintenance costs need to be low
Technologies need to be understood, accepted and used by factory floor personnel
Certainly these criteria are always given and need to be fulfilled. However, since several applications are now being solved and
since more and more companies come up with solutions, these topics become core topics for decision making and will be
essential for the further success of the applications.
It also became obvious by talking to end-users that the type of technology being chosen for use in bin picking applications was
not top priority but rather the criteria listed above.
Market Report Bin Picking
©AMC Hofmann Automation – Market – Competence Page - 13 -
SUCCESSFUL SOLUTIONS
For many years now manufacturers wanting to employ automated bin picking as well as solution providers have found ways to
automate several “bin picking” processes by changing the ground rules.
In the automotive industry today, bins with pins are used for pressed or stamped parts
like doors and hoods that enable automation with standard equipment. Many
processes have been automated by using special inlets in bins or by introducing
specially designed bins, for example, in automotive press shop and body in white
manufacturing. This makes detection and gripping of parts easier.
Sometimes a look at the previous process step can enable a solution by introducing
rules on how to place parts into the bins in the first place. In 2002 the robot
manufacturer Adept Technologies (www.adept.com) came up with its first Anyfeeder
product, a solution that became a great success and standard for many industries and
processes by separating parts before detection and gripping. Picture on the right top,
Adept Anyfeeder Adept, Anyfeeder
SOLUTIONS WITH ADDITIONAL MECHANICAL PART SEPARATION
Many System integrators have started to use different additional mechanical part
separation strategies in order to create a scenario of roughly separated parts to be
picked.
Pictured on the right shows the Schimat, a 6 axes robot based flexible cell using
vision to pick parts from a conveyor as developed by the German company
Schindler Handhabetechnik (www.schindler-handhabe.de). Pictures below show
only a small range of typical products that can be handled with this concept.
Schindler, Schimat
Market Report Bin Picking
©AMC Hofmann Automation – Market – Competence Page - 14 -
More than 40 % of all vendors making a statement on this topic recommend the
use of additional mechanical part separation where it can be technically and
commercially feasible. Table shows also the results divided by original core
competence of the vendors
System integrators
Robot suppliers
Machine vision
STANDARDIZING BIN PICKING TECHNOLOGY
In 2008 Sweden based company Dynamis
(www.dynamis.se) successfully introduced SensActive, a
standard module for part detection in “bin picking”
processes, that is already in use by several automation
solution focused system integrators.
Such smart solutions on the one hand, further
developments of technology, price reduction of standard
components and a much higher level of understanding
on the customer side on the other hand help to match
expectation with capabilities and allows the
implementation and standardization of more and more
“bin picking” applications.
Dynamis, bin picking cell with SensActive technology
0,%
10,%
20,%
30,%
40,%
50,%
60,%
70,%
80,%
90,%
100,%
Overall CC Turnkey CC Vision CC Robotics
Perc
enta
ge o
f com
pani
es in
volv
ed
CC = Core Competence of Supplier
Recommendation for mechnical part separation, by corecompetence of vendor
Recommend part separation
Vendors making statement
Market Report Bin Picking
©AMC Hofmann Automation – Market – Competence Page - 15 -
SOLUTION CONCEPTS
Offering different concepts for the realization of a project, based on the same core components is another important
improvement. For quite some years now systems for robot guidance, such as gluing, assembly or inline measurement, are set-
up with fixed mounted detection units, robot mounted detection units or hybrid set-ups, based on application needs. Several
more concepts based on these three general approaches are today part of the portfolio of turnkey providers.
All interviewed companies support a stationary set-up and around 50% name thisset-up as their preferred choice.
DESCRIPTION STATIONARY CONCEPT
The detection unit is mounted stationary over the bin
Detection can be camera (single or multiple) or scanner based
After picture acquisition the robot can start to move
Calculation of data by the vision system can be done in parallel
After data are processed robot pick the part
Process cycle Cell Layout
Chapter 5, Turnkey Concepts: describes in detail all available and supported concepts.
In chapter 7, Supplier Overview it is shown which of these concepts are supported and recommended by the suppliers.
Part is gripped
Data for gripping becomes available
Robot starts movement
Detection unit aquires picture(s), or scans the bin
Start
BinRobot
Detection
Market Report Bin Picking
©AMC Hofmann Automation – Market – Competence Page - 16 -
TECHNOLOGIES
DETECTION TECHNOLOGIES
The combination of detection technologies, for example classic 2D or 3D machine vision with laser scanning, enables high
degrees of freedom and options to solve an application. All companies interviewed provide or use 2D vision technology.
Numbers below show the distribution of 3D technologies. The overview shows that triangulation and laser scanning are the most
widely used technologies.
The technologies most widely used are triangulation (63%) and Laser scanning(53%).
The vendor overview in chapter 7 also gives the distribution by core competence as well as detailed information of the
portfolio of technologies of the vendors, as far as they have provided this information.
53%
18%
63%
30%23%
8%
38%
3%
30% 28%
0%10%20%30%40%50%60%70%80%90%
100%
Laser scanning Photogrammetry Triangulation Stereometry Time of Flight
Detection Technologies
Supplied and / or supported Not supported
©AMC Hofmann
VISION ALGORITHMS
Machine Vision a
algorithms assure, based on the information provided by the detection unit, that
the other hand th
Most of the 3D detection technologies are operated by standard algorithms, developed and extended from standard 2D machine
vision algorithms. The increasing need for algorithms specifically ded
market to consider this technology
The analysis of point clouds requires a lot of computer processing power and processing time.
Therefore many point cloud algorithms either work on
reduced data or still
data.
For many applications this processing time is not
available. However, some suppliers have specialized
algorithms capable of running at high speed.
Further improvement in algorithms for analysis of point
clouds, as of
Aqsense (
solution tool box to the next level.
Hofmann
VISION ALGORITHMS
Machine Vision algorithms are one of the keys to a successful realization of robot guidance projects. On the one hand vision
algorithms assure, based on the information provided by the detection unit, that
the other hand they can influence the user comfort for system setup enormously.
Most of the 3D detection technologies are operated by standard algorithms, developed and extended from standard 2D machine
vision algorithms. The increasing need for algorithms specifically ded
market to consider this technology
Algorithms in use for bin picking and robot guidance applications that
have been discussed in interviews for this report include:
The analysis of point clouds requires a lot of computer processing power and processing time.
Therefore many point cloud algorithms either work on
reduced data or still need a lot of time for processing
For many applications this processing time is not
available. However, some suppliers have specialized
algorithms capable of running at high speed.
Further improvement in algorithms for analysis of point
clouds, as offered for example by Spanish company
Aqsense (www.aqsense.com
solution tool box to the next level.
Chapter 4, Technologies gives detailed information about the
picking as well as overviews and charts of suppliers and the supported algorithms.
VISION ALGORITHMS
lgorithms are one of the keys to a successful realization of robot guidance projects. On the one hand vision
algorithms assure, based on the information provided by the detection unit, that
ey can influence the user comfort for system setup enormously.
Most of the 3D detection technologies are operated by standard algorithms, developed and extended from standard 2D machine
vision algorithms. The increasing need for algorithms specifically ded
market to consider this technology as viable in the near future.
Algorithms in use for bin picking and robot guidance applications that
have been discussed in interviews for this report include:
Contour based tools
Correlation based tools
Feature extraction
Point cloud analysis
The analysis of point clouds requires a lot of computer processing power and processing time.
Therefore many point cloud algorithms either work on
need a lot of time for processing
For many applications this processing time is not
available. However, some suppliers have specialized
algorithms capable of running at high speed.
Further improvement in algorithms for analysis of point
fered for example by Spanish company
www.aqsense.com), are about to bring the
solution tool box to the next level.
4, Technologies gives detailed information about the
as well as overviews and charts of suppliers and the supported algorithms.
Market Report Bin Picking
Automation
lgorithms are one of the keys to a successful realization of robot guidance projects. On the one hand vision
algorithms assure, based on the information provided by the detection unit, that
ey can influence the user comfort for system setup enormously.
Most of the 3D detection technologies are operated by standard algorithms, developed and extended from standard 2D machine
vision algorithms. The increasing need for algorithms specifically ded
as viable in the near future.
Algorithms in use for bin picking and robot guidance applications that
have been discussed in interviews for this report include:
ntour based tools
Correlation based tools
Feature extraction
Point cloud analysis
The analysis of point clouds requires a lot of computer processing power and processing time.
Therefore many point cloud algorithms either work on
need a lot of time for processing
For many applications this processing time is not
available. However, some suppliers have specialized
algorithms capable of running at high speed.
Further improvement in algorithms for analysis of point
fered for example by Spanish company
), are about to bring the
4, Technologies gives detailed information about the
as well as overviews and charts of suppliers and the supported algorithms.
Market Report Bin Picking
utomation – Market – Competence
lgorithms are one of the keys to a successful realization of robot guidance projects. On the one hand vision
algorithms assure, based on the information provided by the detection unit, that
ey can influence the user comfort for system setup enormously.
Most of the 3D detection technologies are operated by standard algorithms, developed and extended from standard 2D machine
vision algorithms. The increasing need for algorithms specifically dedicated to
as viable in the near future.
Algorithms in use for bin picking and robot guidance applications that
have been discussed in interviews for this report include:
The analysis of point clouds requires a lot of computer processing power and processing time.
4, Technologies gives detailed information about the
as well as overviews and charts of suppliers and the supported algorithms.
Market Report Bin Picking
ompetence
lgorithms are one of the keys to a successful realization of robot guidance projects. On the one hand vision
algorithms assure, based on the information provided by the detection unit, that location
ey can influence the user comfort for system setup enormously.
Most of the 3D detection technologies are operated by standard algorithms, developed and extended from standard 2D machine
icated to the analysis of 3D point clouds has pushed the
Algorithms in use for bin picking and robot guidance applications that
have been discussed in interviews for this report include:
The analysis of point clouds requires a lot of computer processing power and processing time.
4, Technologies gives detailed information about the algorithms used
as well as overviews and charts of suppliers and the supported algorithms.
lgorithms are one of the keys to a successful realization of robot guidance projects. On the one hand vision
location part data is
Most of the 3D detection technologies are operated by standard algorithms, developed and extended from standard 2D machine
analysis of 3D point clouds has pushed the
Algorithms in use for bin picking and robot guidance applications that
The analysis of point clouds requires a lot of computer processing power and processing time.
algorithms used in 3D Robot Guidance
as well as overviews and charts of suppliers and the supported algorithms.
Page
lgorithms are one of the keys to a successful realization of robot guidance projects. On the one hand vision
is available and reliable, on
Most of the 3D detection technologies are operated by standard algorithms, developed and extended from standard 2D machine
analysis of 3D point clouds has pushed the
Aqsense, Match 3D tool
in 3D Robot Guidance, especially bin
Page - 17 -
lgorithms are one of the keys to a successful realization of robot guidance projects. On the one hand vision
available and reliable, on
Most of the 3D detection technologies are operated by standard algorithms, developed and extended from standard 2D machine
analysis of 3D point clouds has pushed the
Match 3D tool
, especially bin
Market Report Bin Picking
©AMC Hofmann Automation – Market – Competence Page - 18 -
HANDLING, ROBOTICS AND GRIPPING
Most bin picking applications allow the use of standard robots and handling systems.
The robot technology used in an application depends on the
application needs, the parts and the site conditions.
The report shows that all types of handling technologies are in
use for bin picking, including delta and SCARA robots.
However, typically 6 axes robots are needed to handle the
degrees of freedom in typical random bin picking applications.
One of the applications shown in the report that uses bin
picking technologies, is the parcel robot.
Handling system and gripper are especially designed for the
need of this application.
Parcel robot by DHL- Discover Logistics
In order to give end-users options to choose the handling system, machine visioncompanies try to support as many robot types as possible.
Only few companies being active in bin picking confirm the design of grippers as core competence. Gripper manufacturers on
the other hand are not active in system integration and the other aspects of bin picking applications.
Companies report that mechanical and vacuum gripping technology are mostlyused / supplied.
Chapter 6, Market Overview shows several applications of bin picking and associated applications in different industries.
Chapter 4 Technologies describes the different robotic & handling technologies.
Chapter 7 Supplier Overview shows which detection technologies are supported by the robot manufacturers and which robot
types are supported by the integrators. Information about gripping is presented by gripping technologies used and vendor
overview of suppliers offering grippers.
Market Report Bin Picking
©AMC Hofmann Automation – Market – Competence Page - 19 -
MARKET OVERVIEW
Bins and boxes are used in many industries, therefore various industries do have a need and interest in this application as well.
However, application parameters and site conditions differ in these industries.
Almost all vendors (98%) are active in the automotive industry.
Random bin picking is associated by most people with the typical
automotive application unloading of un- orientated metal parts.
The automotive industry has always been a driving force for many
technologies, applications products and developments.
A deeper look into the main automotive manufacturing steps shows
where the existing and future potentials for bin picking can be found.
Distribution and adaption of those technologies and applications
developed for the automotive industry has brought automated bin
picking to manufacturers outside of the automotive industry and
pushes further developments.
Besides automotive and their tier suppliers, industries such as
logistics, aerospace, foundry, medical engineering, pharmaceuticals,
food and packaging have already discovered the potentials of
automated bin picking and the required technologies, or are about to
do so.
Picking of gear shafts at Hirschvogel Umformtechnik,
by Fraunhofer IPA
The report shows applications and distribution by the following
automotive segments:
Body in white & press shop
Final assembly
Powertrain
Logistics
Tier suppliers
Chapter 6, Market Overviews shows several existing and future bin picking applications and associated applications in severalindustries such as
Aerospace
Automotive
Food & Packaging
Foundry
Logistics
Medical Engineering
Pharmaceutical
Recycling
Market Report Bin Picking
©AMC Hofmann Automation – Market – Competence Page - 20 -
VENDOR OVERVIEW
Discussions with end-users using bin picking technology or at least having a vested interest in the technology showed very
clearly that in the current phase, where bin picking is just about to become an established application in many industries
customer focus is on choosing complete solutions instead of specifying components and asking somebody to implement the
project.
As in many automation applications it becomes increasingly difficult to find the right solution and the best supplier. Suppliers do
have different focus and different scope of delivery. In order to give a deeper insight into bin picking and the available
components, products and technologies, companies out of robotics, machine vision, and system integration have been
interviewed and are listed in the report. .
Chart below, for example, shows the fields of business named as core competence by the vendors involved.
7 of 8 involved robot manufacturers confirm machine vision as core technology.
Chapter 7 supplier overviews: gives information on the following topics:
Core competence
Fields of activity by region
Detection technology readily available and in
use
Algorithms readily available and in use
Robotics & handling in use
Industries where automated bin picking is
currently in use
Supported solution concepts
The appendix includes:
Supplier contact data
Application and product descriptions
Publications on bin picking and 3D technologies
63%
90%
55%
20%23%
5%
28%
45%
0%10%20%30%40%50%60%70%80%90%
100%
CC Robotics CC MachineVision
CC SystemIntegration
CC Gripping
Vendors by core competence
Core competence
No core competence