Excerpt of Market Intelligence Report Robot Vision 2012

Market Intelligence Report (
arket eport (MIR)

Excerpt of the Market Report
„Robot Vision 2011/2012
2011/2012“
All rights reserved. No part of this excerpt may be reproduced or reprinted without permission in writing from the author.
This prohibition includes copying by a firm for its internal use. © 201 by AMC Hofmann
2012
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under info@amc-hofmann.com .

Robot Vision 2011/2012

AMC HOFMANN
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64629 HEPPENHEIM, GERMANY
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EMAIL: HOFMANN@AMC-HOFMANN.COM
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HOFMANN.COM

Market Intelligence Report Robot Vision 2012

TABLE OF CONTENTS
Introduction ............................................................................................................................................ 3
Why this Report? .......................................................................................................................................... 3
Goals of the market report ............................................................................................................................ 3
Industries involved........................................................................................................................................ 4
Companies involved by Core Competence .................................................................................................. 4
Regions represented .................................................................................................................................... 5
Analysis in this report ................................................................................................................................... 6
Generation of data - Research ..................................................................................................................... 6
Definition of terms* ....................................................................................................................................... 8

1.0 Robot Vision- Technologies ........................................................................................................... 9
1.1 Detection Technologies .......................................................................................................................... 9
1.2 Algorithms ............................................................................................................................................ 11
1.3 Handling ............................................................................................................................................... 12
1.4 Robot Vision Turnkey- Concepts .......................................................................................................... 14
Introduction........................................................................................................................................ 14
Basic concepts for system set-up: ..................................................................................................... 14

2.0 Robot Vision Applications Overview ........................................................................................... 15
2.1 Introduction........................................................................................................................................... 15
2.2 Applications Overview .......................................................................................................................... 15
2.3 Assembly- 2D & 3D & Best Fit.............................................................................................................. 17

3.0 Robot Vision Market Overview .................................................................................................... 19
3.1 Introduction........................................................................................................................................... 19
3.2 Industries Overview .............................................................................................................................. 19
3.3 Aerospace ............................................................................................................................................ 21

4.0 Future Trends in Robot Vision and Machine Vision ................................................................. 22
4.1 Introduction........................................................................................................................................... 23
4.1.1 Technologies ............................................................................................................................ 25
4.1.2 User Requirements .................................................................................................................. 26
4.1.3 Applications .............................................................................................................................. 27
4.1.4 Outlook ..................................................................................................................................... 28

5.0 Vendors Overviews ....................................................................................................................... 29
5.1 Content of The Survey ......................................................................................................................... 29
5.2 Core Competence by vendors .............................................................................................................. 30
5.3 Business Region: distribution by vendors ............................................................................................ 31
5.4 Industries- distribution by vendors ....................................................................................................... 32
5.5 No. of Robot Vision systems installed - overall..................................................................................... 34
Copyright .................................................................................................................................................... 35

©AMC Hofmann Automation – Market – Competence Page - 2 -


INTRODUCTION

WHY THIS REPORT?

Discussions with vendors and users of automation technologies about their needs for information has shown that
the technology of robot vision already plays an important role for automation. New interesting markets as well as
the boost that came with 3D have influenced and grown the world of robot vision and its future development. To
collect, show and analyze all dimensions of robot vision is the goal of this report.

The content topics selected for the report is a direct result of many discussions with end users and vendors of
Machine Vision and vision based automation equipment.

The Market Intelligence Report (MIR) “Robot Vision” therefore addresses all robot vision related topics and
trends.

GOALS OF THE MARKET REPORT

Provide an overview and show a “big picture” of the report´s topics as it is not
available from other sources.

Provide market intelligence, analysis and suggestions, based on data provided
by a large number of key market players.

Provide an overview and outlook on trends in Robot Vision and related
industries and applications where “robot vision” is used.

Keep you up to date on the current status and inform you on new interesting
topics for the world of robot vision.

Provide information and contact data and overviews on vendors, suppliers and
other sources for further information.



INDUSTRIES INVOLVED
In order to get a complete overview of possible trends, applications and needs, the following industries have been
involved in the survey.

Aerospace Electronics & Semiconductor Mining
Agricultural & Forestry Entertainment Packaging
Automotive Food Paper
o BIW & Press shop Foundry Pharmaceuticals
o Assembly Glass Photovoltaic
o Logistics Lab Automation Plastics
o Powertrain Life Science Recycling
o Paint shop Logistics & Transportation Service Robotics
o Tier 0.5 & Tier 1 Medical Engineering Security & Surveillance
Beverage Medical & Health Care Textile
Ceramics Metal Processing Wind Energy
Consumer Goods Military & Defense Wood

COMPANIES INVOLVED BY CORE COMPETENCE
In order to give broad overviews, provide new information and see trends coming down the road from many
directions, the companies involved in the report represent several different core competences emerging in
different regions and many industries as well.
In addition to the company types shown in the chart below, the views of end users are of high importance for our
reports. Before starting a new project the content is first discussed with end users relevant for the topic. Within the
survey end users are questioned as well. Due to the fact that the end users typically do not want to be listed
within the reports we respect that but do use and count their suggestions and input.
The chart below shows the fields of business named as core competence by the vendors involved.

C or e com pe t e nce of th e Com p anie s
100%
8 8 ,9 %
90%
80%
70%
60% 5 2 ,2 % 5 3 ,3 %
50% 4 1 ,1 %
40%
30%
20% 1 5 ,6 %
7 ,8 %
10%
0%
M ac h in e Robotic s & Syste m M ac h in e A u to m atio n L in e Bu ild in g
Vision P o sitio n in g Inte gr atio n Bu ild in g

As already recognized in other reports we see again the strong commitment of “automation
vendors” to Machine Vision. More and more companies having their roots outside Machine
Vision have now made it one of their core competences.



REGIONS REPRESENTED
The chart below shows the regions where the vendors are active and present. The numbers do not differentiate
between legal entities of a company and representatives or partners.

Regions w here vendors are present and active

Australia / Oceania 22,1%

Russia 25,0%

India 32,1%

Japan 29,1%

China 36,6%

Middle East / A frica 21,3%

South A merica 37,8%

North America 63,1%

Southern Europe 57,8%

Central Europe 59,3%

W estern Europe 63,4%

Northern Europe 67,5%

Germany, Austria, Switzerland 77,9%

0% 20% 40% 60% 80% 100%

25% of the companies claim to be already active in Russia, or are from Russia.
21% of the companies claim to be already active in Middle East / Africa



ANALYSIS IN THIS REPORT

Analysis of the data requires a clear understanding of the sources and their technological roots. Therefore each
company was classified by three parameters.

Industry, where active

Core Competence (Technology)

Regions, where active

In order to have the information represented best, multiple selections were possible and allowed.

Questioning companies being active in many different industries brings the benefit to get a very broad information
base, but makes it necessary to take a deeper look at the sources of the information to get a clear understanding
of the results and conclusions.

Counting votes:

In several statistics company votes can be counted several times when they
are active in several industries, regions or markets. Same with the core
competence of a company.
When having core competence in robotics, Machine Vision and system
integration their vote is counted in each section. Overall statistics on such a
topic where all attending companies are counted would show only one vote of
this company.

GENERATION OF DATA - RESEARCH
Data used: All information used is either public or provided and submitted by the companies included in the
survey. Therefore the correctness of the information is obliged to these sources. Data comprised in the report has
been mainly generated by direct interviews conducted with the leaders in this field of automation. Additionally, the
results of further 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 and comprehensive overview.

The survey:

Companies attending the survey have been asked to rate all topics shown in
this report, based on expected future potential for growth. Available ratings
have been:
None
Low
Average
High
Multiple selections have not been allowed.



Data handling and analysis within the tables and charts:

Due to the fact that not all information or statements were always given
by all of the companies, the numbers in the charts do not necessarily add
up to 100%

Note:

In order to give a broad and complete overview information in this report
are not limited to the information provided by of the questionnaires.
Material available in form of presentations or from websites is added as
well. All sources used are listed in the appendix.

Methods: Data generation of information was done by the following methods

Web research

Literature research

Direct personal communication with vendors and end users

Questionnaires sent out to vendors

Questionnaires sent out to end users

Geography: In order to get an international overview, companies from the following regions have been involved
in this survey:

Europe

North America

Asia

India

Russia

Australia & New Zealand

Confidentiality: All information / data published in this report has either been confirmed or publicly released by
the providing companies for publishing in this report or derived from public sources.



DEFINITION OF 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- Abbreviation for „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 from the
machine vision point of view.

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 of the car manufacturers.

Powertrain- Powertrain is the term for automotive manufacturing of parts that are used in underbody frame and
engine and transmission. 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.

UAV- Unmanned Aerial Vehicle guided either by on board sensors and processors or guided remotely through a
man-machine interface.

UGV- Unmanned Ground Vehicle, guided either by on board sensors and processors or guided remotely through
a man-machine interface.

General Industries- Especially companies supplying equipment to “industry” classify and structure the
industries. Due to the large amount of industries many vendors structure is based on their business and their
focus. In many cases the term General Industries is used to describe and summarize many industries that are not
covered by the other industries classified. So General Industries includes different content depending on the
company you are talking to.

Robot Vision- The term Robot Vision depends on the terms Robot and Vision (for Machine Vision). This brings
us to the question - what is the definition of a robot? Pictures below show some vehicles and mechanical
devices described as robots.

To come to a common understanding and conclusion on what is a robot here is the explanation from Wikipedia:
“A robot is a mechanical contraption which can perform tasks on its own, or with guidance.”

So the definition of Robot Vision, within our reports, is based on this definition which remains a little fuzzy. Robot
Vision is the automated guidance of a robot, handling device or moving vehicle- guidance can be by Machine
Vision technology but does not have to be limited to that. Other technologies for example radar or ultrasonic
technology can be used as well.



1.0 ROBOT VISION- TECHNOLOGIES

The more challenging an application is, the more important the clear understanding of all involved sub-
systems becomes. Robot Vision applications consist of many technologies and components that are
more or less important depending on the specific application.
Therefore this report explains the following topics, with a strong focus on the machine vision topics.

Detection (Machine Vision / Scanning)
Algorithms (Machine Vision)
Handling & Robotics
Basic concepts for system integration

1.1 DETECTION TECHNOLOGIES
Starting in the semiconductor and electronics business in the late 1980´s machine vision was focused
on 2D position measurement mainly in combination with axes handling systems and more and more
SCARA robots. In the late 1990´s when machine vision companies introduced the first 3D vision
technologies. Applications where machine vision systems guided 6- axes robots started to be popular.

At this time, companies like Perceptron (www.perceptron.com ), LMI Technologies (www.lmi.com ),
Isra Vision (www.isravision.com ), VMT (www.vmt-gmbh.com ), HGV Vosseler (www.hgv.de) and
Vitronic (www.vitronic.com ) successfully developed the first 3D vision technologies for robot guidance
using Photogrammetry, Laser triangulation and Stereometry. This was done primarily to meet the
automation needs of the automotive industry.

At the same time, sensor companies such as Sick, Leuze Electronics, Micro-Epsilon and Keyence
started to introduce Laser scanning mainly in the field of displacement sensors.

Time of Flight (ToF) cameras have recently become available and are getting more and more popular
for machine vision applications from vendors such as Baumer, PMD, Mesa and Canesta.

In many business fields different technologies and concepts compete, just look for example at
communication interfaces. In 3D machine vision technology this is different. All of these technologies
have their strengths and weaknesses and therefore are needed. Sometimes the right combination of
several of these technologies can lead to the best solution.



Detection Technologies:

Machine Vision (2D) Stereometry (3D)
Machine Vision (2 ½ D) Laser Scanning (3D)
(Laser-) Triangulation (3D) Time of Flight (3D)
Photogrammetry (3D)

Combining several of these technologies and different solution concepts offers lots of
options enabling a suitable solution for an application.

3D Detection Technology overall

Visual Servo 14,4%

Time of Flight (ToF) 20,0%

3D with one camera 24,4%

3D: Scanning 28,9%

3D: Stereometry 26,7%

3D: Triangulation (Sheet of light) 48,9%

3D: Photogrammetry 12,2%

0,0% 20,0% 40,0% 60,0%

The chart shows the distribution of the 3D technologies over all the companies
participating the survey. This includes line builders, machine builders and robot
manufacturers as well.

The full report provides more topics, statistical data, analysis, charts, and overviews, as well as
articles and links.



1.2 ALGORITHMS
Machine Vision algorithms are one of the keys to a successful implementation of robot guidance
projects. On the one hand they assure, based on the information provided by the detection unit, that
part position and dimension data is accurate and reliable, on the other hand algorithms can
enormously influence the user comfort for system set-up. In the 90´s most algorithms, sometimes
working on binary images, have been based on blob (binary large object) detection, or edge detection.
More sophisticated was grey scale correlation, however, this tool hasn´t been capable to detect a part
in all possible rotational variations.
At the end of the 1990´s the first algorithms being able to work at complete 360° rotation, either
correlation or contour based, became available. At this time Cognex Corporation developed algorithms
with the ability to measure the scale of a repeatable object and in this way determine rough “z”-
information (distance to the top of the part and by deduction the height of the part). In the following
years these algorithms became faster, easier to use, control/parameterize and available from many
machine vision software suppliers.

The chart shows the distribution of the algorithms over all participants of the survey.
Vendors were free to choose more than one option.

Detection Algorithms
60,0%
45,6%
42,2%
38,9%
40,0%
32,2%

20,0% 13,3%

1,1%
0,0%
Contour Correlation Feature Cloud of Company Others
based based extraction points own Tools

articles and links.



1.3 HANDLING
Highly standardized robots can be chosen based on application and product needs. Depending on
market and application needs the different robot types do have more or less market shares.
Some of the robot manufacturers have focused early on the combination of robot and vision systems.
One pioneer here definitely was the company Adept Technology. Among the leading 6- axis robot
manufacturers Fanuc Robotics is most focused on this topic.
In addition to the robots described below cartesian systems are used in many applications and inside
machines as well.

6- axes robots
In 1973 Kuka develops the first industrial robot
with six electromechanically driven axes.
Today six axes robots are available from many
vendors, for different applications, with different
accuracies and payloads of up to 1000 kg
(Kuka 1000 titan).

6- Axes robot, Kuka Robotics

SCARA robots
The first SCARA (Selective Compliant
Assembly Robot Arm) robot was developed in
1981 at the University of Yamanashi under the
guidance of Hiroshi Makino.
SCARA robots are mainly used in assembly
processes of light and small objects.

SCARA Robot, Epson

Delta robots
The delta robot was invented in the early 1980s
by Reymond Clavel at the Ecole Polytechnique
Federale de Lausanne (EPFL, Switzerland).
Delta robots are mainly used to handle light and
small objects at very high speed.

Delta Robot, Adept Quattro



Cartesian coordinate robot

A linear robot uses three axes. They move in a
straight line rather than rotate and are at right
angles to each other.

One of the advantages of this mechanical
arrangement is to simplify the robot control arm
solution.

Cartesian robots sometimes are also called
Gantry robots and they often are quite large.

Popular applications for cartesian robots are
computer numerical control machines (CNC
machine), cutting machines and fast pick and
place systems.. Gantry handling, Güdel

The chart below shows the distribution of robot use among the participants of the survey.

Handling used / supported
Kawasaki 13%
Stäubli 23%
Reis 3%
Nachi 4%
Motoman 29%
Mitsubishi 11%
Kuka 43%
Güdel 6%
Fanuc 36%
Epson 13%
Denso 11%
Comau 8%
Adept 12%
ABB 39%
0% 10% 20% 30% 40% 50%



1.4 ROBOT VISION TURNKEY- CONCEPTS

INTRODUCTION

Beyond the specific part to determine the position of an object or a feature of an object, various
technical processes provide many differences for the implementation of a Robot Vision system. These
are both customer specific as well as process specific.
Site conditions as well as other requirements vary widely and make it sometimes impossible to
implement an application by using one unique concept.
As we know from many applications such as palletizing, glueing or robot guided assembly, different
cell layouts enable the realization of projects with different site conditions based on the same
components and subsystems.
For customers looking for solutions of several applications with different parts, the portfolio of available
technologies and concepts can be a key factor for decision making.
Many of the vendors already support stationary, robot mounted and hybrid concepts. Those concepts
and some variants are described later in this chapter.

BASIC CONCEPTS FO R SYSTEM SET-UP:
There are three basic concepts to set-up a robot vision cell:

Fixed mounted (stationary)
Robot / Handling mounted (moving)
Hybrid (combination of stationary and moving)

The following explanations and description are based on handling applications such as de-palletizing,
pick and place or bin picking.

articles and links.



2.0 ROBOT VISION APPLICATIONS OVERVIEW

2.1 INTRODUCTION
Robot Vision as basic technology as well as an application, can be used across many markets,
industrial and non- industrial. Sometimes it becomes difficult to define where to use the term industrial.
However, our goal is to cover as much fields of application where Robot Vision technology is in use or
can be used in the near future as possible. The chapter "Future Trends" shows the expectation of the
vendors for the applications addressed in this report.
For some case examples, especially when talking about new R&D projects and other prototypes only
limited information can be distributed due to confidentiality. In these instances this report refers to the
companies working on the project.
Many times turnkey suppliers, either system integrators or OEM´s (original equipment manufacturers),
have focused on specific applications and technologies, for example on handling, assembly, glueing
and many more. Technology, product and component suppliers also always have to look for other
markets, applications and regions where their technologies and products can be used. Therefore to
get the most comprehensive overview of applications for Robot Vision integrators, line builders and
their suppliers have been interviewed. For verification of the results as well as to complete the picture,
end users in several industries have also been interviewed directly.
The pre-selection of industries offered in the questionnaire was focused on markets where the use of
Robot Vision technology is already confirmed or at least planned for near term use. Multiple selections
have been allowed.
Suppliers were asked to mark the industries where they are already active in. This was not limited to
industries where they are active in with Robot Vision. The option was given to the vendors to add
applications relevant to Robot Vision.
Chapter 2.2 shows an overview of the applications and the distribution by activities of the companies.
Starting from chapter 2.3., applications are shown and described with reference to robot vision
technology.

2.2 APPLICATIONS OVERVIEW
In order to get a complete overview of possible trends, applications and needs, the following
applications have been included in the survey.

Assembly 2D Outdoor Guidance Seam Tracking

Assembly 3D Pick & Place 2D Service Robotics

Assembly 3D Best Fit Pick & Place 3D UAV

Bin Picking RV & Inspection 2D UGV

Baggage Handling RV & Inspection 3D Visual Servo

Palletizing / De- Palletizing RV 2D & Identification

Racking / De- Racking RV 3D & Identification



Chart below shows the applications covered by the survey and the distribution of activities of the
companies included in the survey.

Applications where vendors are active in

Visual Servo 22,2%

UGV 6,7%

UAV 5,6%

Service Robotics 14,4%

Seam Tracking 18,9%

RV(3D) & Identification 25,6%

RV(2D) & Identification 28,9%

RV & Inspection(3D) 31,1%

RV & Inspection(2D) 34,4%

Pick & Place (3D) 44,4%

Pick & Place (2D) 54,4%

Outdoor Guidance 6,7%

Racking / De-Racking 25,6%

Palletizing / De- Palletizing 42,2%

Baggage Handling 8,9%

Bin Picking 36,7%

Assembly 3D, Best Fit 22,2%

Assembly 3D 40,0%

Assembly 2D 40,0%

0% 10% 20% 30% 40% 50% 60%

Today the 2D Robot Vision applications still have a stronger representation in the
markets. However, the chapter "Future Trends" shows the expectation of the companies
and the forecasted changes.



2.3 ASSEMBLY- 2D & 3D & BEST FIT
Assembly is a huge field of application for
machine vision and robotics. Great many
industries and markets provide potential
for these applications.
Robot Vision for 2D Assembly is available
from almost all vendors, Vision vendors
as well as Robot manufacturers. 3D
assembly applications are much more
challenging. Therefore most of these
applications have required experienced
machine vision system integrators with Picture by Inos Automationssoftware, Best Fit for Panels, Glass
strong competence in vision and robotics. Modules, Cockpit and Front End Assembly.
Inos Automationssoftware is one of those innovative companies having introduced the HPFIT
technology (high precision fitting). The picture shows the assembly of glass modules, a typical
application in the automotive industry where the 3D Best Fit technology is required.
Best Fit is the idea of assembling two imperfect parts and get an optimized result. For many
automotive assembly applications perfect means equalized gaps around the fitted part. However, the
definition of "perfect" is different from one manufacturer to the other.
Especially the automotive industry is a huge field for 3D assembly applications. One will find roof
assembly, door assembly, glass assembly, cockpit assembly, seat assembly and wheel assembly to
name some of them.

Below please find information provided by the companies within the survey

All companies (100%) active in best fit assembly see machine vision as their core
competence.
The strongest representation of companies with their core competence in robotics is found in
2D assembly (66%).

Assembly by Core Competence
97,2% 100,0% Assembly 2D Assembly 3D Assembly 3D, Best Fit
100,0% 94,4%

80,0%
66,7%
58,3% 58,3% 60,0%
60,0% 50,0% 52,8%
47,2% 50,0%
44,4%
40,0%
27,8% 30,0%
19,4% 13,9% 15,0%
20,0% 11,1%

0,0%
Machine Vision Robotics System Integration Machine building Automation Line building
Companies

Future trends: 43% of all companies participating in the survey expect a high potential for
growth for the 3D assembly application, 53% expect a high potential for 3D assembly Best Fit.
Future trends: companies that rate best fit assembly "high" are mainly active in Automotive,
Foundry and Aerospace.



Companies in this survey active in 2D assembly:

ABB Robotics Fanuc Robotics Motoman Robotics
Adept Technology Fatronik Octum
Advenovation Grenzebach Profactor
AIC S.A. Hahn Automation RobotWorx
AMT HGV SAC
Avalon IBS Scholz SuE
BMH Ilorya Sick IVP
Cognex ImagingLab SIR
Comau Kawasaki Robotics Visionic
Compar KeySysTech VisionTools
Edixia LMI ViTec
Epson Robotics MVTec

Assembly 2D: handling Assembly 2D: detection
2D Robot Vision 92%
ABB 56%
Adept 22% 2 1/2D Robot Vision 67%
Comau 14%
3D Robot Vision 78%
Denso 19%
Epson 22% 3D Photogrammetry 17%
Fanuc 44%
3D with one camera 47%
Güdel 11%
Kuka 58% 3D Scanning 25%
Mitsubishi 17%
3D Stereometry 33%
Motoman 39%
Nachi 8% 3D Triangulation 56%
Reis 3%
Time of Light 28%
Stäubli 36%
Kawasaki 19% Visual Servo 17%
0% 20% 40% 60% 80% 0% 20% 40% 60% 80% 100%

Assembly 2D: industries overview
40% 37% 36%
35% 30% 30%
30% 26% 27%
22% 23% 22%
25% 20% 21% 20%
19% 18% 19% 19%
20% 16% 16% 17%
14% 14%14% 14% 13%
15% 11% 12% 11% 11%
8% 9%10%
10% 7% 6% 6%
4% 4%
5% 1% 2%
0%

articles and links.



3.0 ROBOT VISION MARKET OVERVIEW

3.1 INTRODUCTION
Robot vision is a basic technology as well as an application and can be used across many industries.
Consequently there is a great number of markets and industries to be discovered and conquered by
machine vision. In order to give a broad overview on the industries and markets already discovered,
the survey results depicted in the graph on the next page are drawn from European and North
American turnkey suppliers as well as product and component suppliers.
Turnkey suppliers, both system integrators or OEM´s (original equipment manufacturers), often are
focused on specific industries; product and component suppliers on the other hand always have to
look for other industries and regions where their existing products can be used. Therefore, to get a
most comprehensive overview of the potentials for robot vision integrators, line builders and their
suppliers have been interviewed. For verification of the results as well as to complete the overview,
end users in several industries have also been interviewed directly.
The pre-selection of industries offered in the questionnaire was focused on industries where the use of
robot vision technology is already confirmed or at least planned for near term use. Multiple selections
have been allowed.
Suppliers were asked to mark the industries where they are already active in. This was not limited to
industries where they are active with robot vision. The option was given to the vendors to add
industries relevant to robot vision.
Chapter 3.2 shows an overview of the industries and the distribution by activities of the companies.
Starting from chapter 3.3., industries and markets are shown and described with reference to robot
vision technology.

3.2 INDUSTRIES OVERVIEW
In order to get a complete overview of existing and future trends, applications and needs, the following
industries have been involved in the survey.

Aerospace Electronics & Semiconductor Mining
Agriculture & Forestry Entertainment Packaging
Automotive Food Paper
o BIW & Press shop Foundry Pharmaceuticals
o Assembly Glass Photovoltaic
o Logistics Lab Automation Plastics
o Powertrain Life Science Recycling
o Paint shop Logistics & Transportation Service Robotics
o Tier 0.5 & Tier 1 Medical Engineering Security & Surveillance
Beverage Medical & Health Care Textile
Ceramics Metal Processing Wind Energy
Consumer Goods Military & Defense Wood



The chart below shows all industries & markets covered by the survey and the distribution of activities
of the companies included in the survey.

Industries where participants are active
Wood 15,6%
Wind Energy 14,4%
Textile 10,0%
Security & Surveillance 16,7%
Recycling 7,8%
Plastics 31,1%
Photovoltaic 24,4%
Pharmaceutical 36,7%
Paper 13,3%
Packaging 48,9%
Mining 4,4%
Military & Defense 15,6%
Metal & Steel 27,8%
Metal Processing 42,2%
Medical & Health Care 26,7%
Medical Engineering 25,6%
Logistic & Transportation 34,4%
Life Science 7,8%
Lab Automation 12,2%
Glass 27,8%
Foundry 32,2%
Food 40,0%
Entertainment 12,2%
Electronics & Semiconductor 23,3%
Consumer Goods 32,6%
Ceramics 21,1%
Beverage 20,0%
Automotive T0,5 & T1 48,9%
Automotive Paint shop 23,3%
Automotive Assembly 57,8%
Automotive Logistics 33,3%
Automotive Powertrain 55,6%
Automotive Body in white 42,2%
Automotive Press shop 34,4%
Automotive 80,0%
Agriculture & Forestry 10,0%
Aerospace 41,1%

0,0% 20,0% 40,0% 60,0% 80,0%

The chart shows that 80% of all companies covered in the report are active in the
Automotive industry.

Outside the Automotive industry, Packaging (49%), Aerospace (41%), Food (40%) and
Metal Processing (42 %) have the strongest representation.

Electronics & Semiconductor have been selected by only 23% of the companies. This
can be explained by the clear focus of the study on robot vision and a strong
representation of system integrators. Semiconductor and Electronics mainly use
standard machines with integrated vision functionality.



3.3 AEROSPACE
Compared to other industries such as Automotive,
Packaging, Electronics, Photovoltaics or
Pharmaceuticals, the automation grade in aerospace is
much lower. However, the number of companies
participating this survey being active in Aerospace is
relatively high. This probably is caused by the strong
representation of 3D robot vision in this survey.

One of the reasons for the lower grade of automation is
the much lower production rate of airplanes compared
for example to cars. And the reason is the enormous
size of an airplane, making many automation tasks
difficult. However, the need for repeatable inspection,
high accuracy in production and the goal to ease the Picture by Brötje Automation, vision guided riveting
heavy work are driving factors for automation. machine for aircraft and helicopter production.

The placement and inspection of rivets is one example where the automation already is standard since many
years. However, so far specialized machines and not robots do the work.

The automated painting is another potential robot vision application considered in the aerospace industry. This
application is already standard in the automotive industry, but also in wind energy for the automated painting of
rotors of wind mills (see the chapter wind energy). There are also many typical powertrain applications that are
used for aerospace parts as well, especially when suppliers work for both industries, aerospace and automotive.

Additional opportunities can be found in related markets "outside" aerospace manufacturing, such as the
guidance of the airplane for parking assistance, but also in related industries such as UAV, Military & Defense and
Service Robotics.

Below please find information provided by the companies within the survey
Compared with other industries and Aerospace by Core Competence
applications aerospace shows strong 80,0%
71,4%
activities of the line builders (71%) and 70,0%
machine builders (57%). 60,0% 57,1%
51,1%
Machine vision core competence is only 50,0% 43,8% 45,8% 45,9%
represented with 44%. 40,0%
30,0%
Applications with strongest representation:
20,0%
Pick & Place 2D 10,0%
Pick & Place 3D 0,0%
Machine Robotics System Machine Automation Line
Palletizing / De- Palletizing Vision Integration building building
Companies

Handling: Kuka (59%), Fanuc (59%) and ABB (50%) have the strongest representation among the
system integrators active in Aerospace.

Vision Systems: Sick (27%), Dalsa and Fanuc (both 22%) have the strongest representation
among the companies active in Aerospace.

Smart Cameras: Cognex Insight (32%) is the Smart Camera with the strongest representation at
the system integrators active in Aerospace.

MV Software: The vision software products most commonly used by companies active in
Aerospace are Cognex (22%) and National Instruments (19%).

MV Sensors: The vision sensors most used by system integrators active in Aerospace are by
Sick, Baumer and Automation Technology.



Companies in this survey which stated to be active directly in Aerospace:

ABB Robotics Grenzebach Automation Scholz SuE
Advenovation HGV SIR
AIC S.A. ibea Tattile
AMT ImagingLab Tec Automation
Aqsense Inos ThyssenKrupp Krause
AV&R ISRA Tordivel
BiBa Bremen Kuka Robotics Vision++
Blumenbecker Prag MVTec Visionic
Comau Motoman Robotics Visio Nerf
Dalsa National Instruments VisionTools
Fanuc Robotics Orus Integration VRSI
Fatronik PPT
Fraunhofer RobotWorx

Aerospace: Applications Handling: by Integrators active in Aerospace

Kawasaki 23%
Visual Servo 11% Stäubli 27%
Seam Tracking 14%
Reis 5%
Nachi 9%
RV3D & Identification 18% Motoman 45%
Mitsubishi 14%
RV 2D & Identification 18% Kuka 59%
Güdel 9%
RV & Inspection 3D 18%
Fanuc 59%
RV & Inspection 2D 18% Epson 14%
Denso 9%
Pick & Place 3D 24% Comau 18%
Adept 14%
Pick & Place 2D 26% ABB 50%
Outdoor Guidance 3% 0% 20% 40% 60% 80%
Racking / De-Racking 18% Aerospace: 3D Technologies
Pelletizing / De- Palletizing 22% Photogrammetry 24,3%
Baggage Handling 8%
Triangulation 62,2%
Bin Picking 21%
Stereometry 37,8%
Assembly 3D, Best Fit 14%
Scanning 40,5%
Assembly 3D 24%

Assembly 2D 20%
3D with one Camera 37,8%

0% 10% 20% 30% 0% 10% 20% 30% 40% 50% 60% 70%

Vision Systems used by Integrators active in Aerospace
40% 36%
35%
30% 27%
25% 23%
20% 18%
14% 14% 14%
15%
9% 9% 9%
10%
5% 5% 5% 5% 5% 5% 5% 5% 5% 5% 5% 5% 5% 5% 5% 5%
5%
0%
0%

articles and links.



4.0 FUTURE TRENDS IN ROBOT VISION AND MACHINE VISION

4.1 INTRODUCTION
When I started in Machine Vision in 1996 at Cognex Corporation, Machine Vision was a great new
world of interesting visions and opportunities.

Trying to explain what Machine Vision is, I used to summarize that it is the optical, camera based
technology for automated inspection and guidance. My explanation was always to describe that nearly
everything around us has come into contact with Machine Vision during its production. The tooth brush
and the shampoo you are using in the morning, the cookies, eggs and all the packaging you are
having on your breakfast table. The car you are using to go to work, even the ticket you are getting for
driving too fast is connected to Machine Vision in one or the other way.

Today, almost 15 years later, looking back to all the
“Visions” we had in the 90´s, many of them became
real – even standard. In addition many new “visions”
have been born and grew into new dimensions.

Looking for a nice picture for “Future User Interface” for
this report I found many named as “Minority Report
Interface”- the one used by Mr. Tom Cruise. A movie –
still a vision?

Outside the world of so called “Industrial Machine
Vision” drones are patrolling in the sky, UGV´s are
used to explore the deep sea and repair oil lecks and a
mowing robot has become our favorite Christmas
present.

Miniaturized components are used for surgeries inside
our body. Advanced algorithms are used to classify
cancer and identify human faces in Facebook. Picture, from movie Minority Report

So you see the explanation for “Machine Vision” still
describes great many different applications around us –
however, the Machine Vision technologies already
have conquered many fields outside the “typical”
industrial fields.

In the last 15 years prices of components went down, but labor cost either increased or stayed the
same. Therefore it was necessary also to work on the “ease of use” for the standardization of
components, interfaces and MMI. Vendors, who were not typical Machine Vision companies entered
into the Machine Vision fields. Those companies came up with user friendly, easy to use and
inexpensive products for many applications, enabling automation companies and end- users to install
and set- up these solutions by themselves.

Machine Vision is influenced increasingly by trends and technologies becoming available from
consumer markets. This “evolution” is on-going. In the early times special hardware was needed and



image information needed to be reduced in order to achieve acceptable processing times. Today
powerful hardware and sophisticated algorithms are available at relatively low cost.

Many changes that were expected did happen – others didn´t or we are still waiting for breakthroughs.

Looking from today back on the last 20 years but also ahead into the near future, it is obvious that the
world of Machine Vision offers enough space and opportunities for many different technologies,
products and vendors.

This report is about several of these hot topics being discussed today especially when related to
robotic automation. Interestingly two of those topics “Cloud Computing for Machine Vision “ and
“Computational Cameras” have been the center of key level speeches at the EMVA conference in
Amsterdam in May 2011.

During this conference Ramesh Raskar, Associate Professor at MIT Media Lab, was talking about the
th
10 dimension and looking around a corner to explain computational cameras. Others are looking for
the computational power for processing large number of data for full 3D in “the Cloud” (the late Mr.
Jobs had declared as our future for data storage and processing).

Reason enough to create this Report and present useful information for everybody active or interested
in Future Trends in Machine Vision, but has never been at MIT.



4.1.1 TECHNOLOGIES
Within the survey companies where asked about their expectation of several topics for the near future
of Machine Vision / Robot Vision. The topics that have been addressed were collected from
discussions with users and vendors of Machine Vision and automation equipment and solutions.

Technology Topics that have been addressed within the survey :
Increase in camera dynamic range
Computational cameras
Real- time detection, moving objects
Use of color information
Analysis of point clouds
Increase in camera resolution
Cloud Computing for Machine Vision
Vision system integrated into the “robot controller”

Participating companies rated the topics in one of the four categories:

Low Average High
None

Multiple selections have not been allowed

"High" rating for Technologies

Increase in camera dynamic range 31%
Computational cameras 31%
Real- time detection, moving objects 50%
Further system / product price reduction 43%
Use of color information 39%
Analysis of point clouds 46%
Increase in camera resolution 24%
Cloud computing for Machine Vision 19%
Vision system integrated into the "Robot Controller" 55%

0% 10% 20% 30% 40% 50% 60%

The analysis of point clouds as a topic strongly dedicated to 3D imaging gets one of the
highest rankings with 46% of the votes.
The Integration of vision systems into robot controllers is a topic for many years and
already utilized by several companies, but it remains a very important topic for the
future (55%).
Real- time detection / tracking of moving parts is ranked high by 50% of the
participants.



4.1.2 USER REQUIREM ENTS
Within the survey companies where asked about their expectation of several topics related to user
requirements for the near future of Machine Vision / Robot Vision. The topics that have been
addressed were collected from discussions with users and vendors of Machine Vision and automation
equipment and solutions.

User Requirements that have been addressed :
User Interface / MMI
Processing speed
Data mining SPC
System accuracy
System reliability and robustness
Miniaturization of components
Price / performance ratio
Responsiveness of supplier to application specific requests
Responsiveness of supplier to service and support requests


Low Average High
None


"High" rating of User Requirements

Responsiveness of supplier to service and support requests 42%

Responsiveness of supplier to application specific requests 59%

Price / Performance ratio 62%

Miniaturization of components 13%

System reliability / robustness 74%

System accuracy 58%

Data mining & SPC 10%

Processing speed 51%

User Interface 66%

0% 10% 20% 30% 40% 50% 60% 70% 80%

System reliability and robustness, the user interface, and the price / performance ratio
got the highest rating for “High Potential” overall.
Most of the topics addressed do have relatively high ratings. Only data mining and the
miniaturization of components are rated relatively low.



4.1.3 APPLICATIONS
Within the survey companies where asked about their expectation of several topics related to user
requirements for the near future of Machine Vision / Robot Vision. The topics that have been
addressed were collected from discussions with users and vendors of Machine Vision and automation
equipment and solutions.

Applications that have been addressed :
Assembly 2D RV & Inspection 2D
Assembly 3D RV & Inspection 3D
Assembly 3D Best Fit RV 2D & Identification
Bin Picking RV 3D & Identification
Baggage Handling Seam Tracking
Palletizing / De- Palletizing Service Robotics
Racking / De- Racking UAV
Outdoor Guidance UGV
Pick & Place 2D Visual Servo
Pick & Place 3D


None Low Average High

"High" rating for Applications
Visual Servo 7%
UGV 25%
UAV 11%
Service Robotics 26%
Seam Tracking 14%
RV(3D) & Identification 46%
RV(2D) & Identification 24%
RV & Inspection(3D) 53%
RV & Inspection(2D) 41%
Pick & Place (3D) 50%
Pick & Place (2D) 27%
Outdoor Guidance 32%
Racking / De-Racking 18%
Pelletizing / De- Palletizing 33%
Baggage Handling 5%
Bin Picking 46%
Assembly 3D, Best Fit 50%
Assembly 3D 46%
Assembly 2D 18%

0% 10% 20% 30% 40% 50% 60%

The combination of 3D Inspection and Robot Guidance got the highest rating for the
future.
Overall the expectation shows a clear shift to applications that use 3D technology.



4.1.4 OUTLOOK
Machine Vision traditionally was focused on the industrial markets. Looking back to the 90´s market
leading vendors used this message in their naming such as “Cognex - Vision for Industry”. In the last
years the Machine Vision business changed. It is developing more and more into other markets and
applications outside the traditional industrial business.
At the same time technologies and trends from other industries, especially consumer electronic
markets influenced the Machine Vision business and helped to open new areas in the traditional
industrial markets.
In the moment we see the world become 3- dimensional – a trend that is pushed from several
directions: Machine Vision, industrial measurement and consumer markets such as gaming and video
entertainment as well. This is only one example showing how things come together, influencing the
whole business, changing markets and their vendors.
Therefore it is of high importance to monitor all these developments and changes in technologies and
markets. Market Intelligence Reports help you to keep track, be prepared and stay on top of these
changes and developments.

articles and links.



5.0 VENDORS OVERVIEWS

5.1 CONTENT OF THE SURVEY
Data in this report have been generated by a questionnaire sent to and returned by the companies
and by additional research. Research methods have been already listed in “Chapter 1, Introduction”.
Companies not having responded to the survey and not providing public information related to the
topics are not included in these overviews.
The following chapters show the information provided by the participants or collected within research
and provide different analysis of the data. The Report summary gives you some selected charts. The
full report provides more extensive overviews and information.

Topics that have been addressed in the survey :

Core competence of vendors

Business activities of the vendors

Regions where vendors are active

Industries where vendors are active

No. of Robot Vision systems installed, overall / per year

Detection Technologies, available or supported

Detection Algorithms

Applications where vendors are active

Application / Customer references

Robots & Handling systems used and supported

Vision systems used and supported

Smart Cameras used and supported

Machine vision software used and supported

Machine vision sensors used and supported

Future Trends- Applications

Future Trends- Technologies

Future Trends- User Requirements

Man Machine Interface (MMI)

Robot Vision system architecture

Multiple selections have been allowed for almost all questions



5.2 CORE COMPETENCE BY VENDORS
Information requested:

Which of the following fields of business does a vendor define as core competence?

Machine Vision Machine Building
Robotics & Positioning Automation
System Integration Line Building

Multiple selections have been allowed

89 % of the companies naming system integration as core competence also named
machine vision.

81 % of the companies naming robotics & positioning as core competence also named
machine vision.

Core competence of the Companies
100%
88,9%
90%
80%
70%
60% 52,2% 53,3%
50% 41,1%
40%
30%
20% 15,6%
7,8%
10%
0%
Machine Robotics & System Machine Automation Line Building
Vision Positioning Integration Building



5.3 BUSINESS REGION: DISTRIBUTION BY VENDORS

In which regions is each vendor active? Regions are defined as follows

Germany, Austria, Switzerland Middle East, Africa (MEA)
Northern Europe China
Western Europe Japan
Central Europe India
Southern Europe Russia
North America Australia / Oceania
South America

Multiple selections were allowed.

Due to the focus of the survey Europe, especially the German speaking region have
the strongest representation. The numbers also show how global many of these
companies act (or probably have to act to fulfill the requirements of the markets and
customers).

Regions where vendors are present and active

Australia / Oceania 22,1%

Russia 25,0%

India 32,1%

Japan 29,1%

China 36,6%

Middle East / Africa 21,3%

South America 37,8%

North America 63,1%

Southern Europe 57,8%

Central Europe 59,3%

Western Europe 63,4%

Northern Europe 67,5%

Germany, Austria, Switzerland 77,9%

0% 20% 40% 60% 80% 100%



5.4 INDUSTRIES- DISTRIBUTION BY VENDORS

In which industries are the vendors active? Multiple selections were allowed.

Aerospace Entertainment Paper
Agriculture & Forestry Food Pharmaceuticals
Automotive Foundry Photovoltaic
o BIW & Press shop Glass Plastics
o Assembly Lab Automation Recycling
o Logistics Life Science Service Robotics
o Powertrain Logistics & Transportation Security & Surveillance
o Paint shop Medical Engineering Textile
o Tier 0.5 & Tier 1 Medical & Health Care Wind Energy
Beverage Metal Processing Wood
Ceramics Military & Defense
Consumer Goods Mining
Electronics & Packaging
Semiconductor

The pre-selection of industries offered in the questionnaire was focused on industries where robot
vision systems and technologies are already confirmed or at least planned for near term use.
Suppliers were asked to mark the industries where they are already active in. The option was given to
the vendors to add industries relevant to robot vision.

The Automotive industry has the strongest representation within the industries.

Within the Automotive industry most of the companies are active in Assembly,
Powertrain and in Tier 1.

Outside the Automotive industry Metal Processing, Aerospace, Food and Packaging
have the strongest representation.



Industries where vendors are active
Wood 15,6%
Wind Energy 14,4%
Textile 10,0%
Security & Surveillance 16,7%
Recycling 7,8%
Plastics 31,1%
Photovoltaic 24,4%
Pharmaceutical 36,7%
Paper 13,3%
Packaging 48,9%
Mining 4,4%
Military & Defense 15,6%
Metal & Steel 27,8%
Metal Processing 42,2%
Medical & Health Care 26,7%
Medical Engineering 25,6%
Logistic & Transportation 34,4%
Life Science 7,8%
Lab Automation 12,2%
Glass 27,8%
Foundry 32,2%
Food 40,0%
Entertainment 12,2%
Electronics & Semiconductor 23,3%
Consumer Goods 32,6%
Ceramics 21,1%
Beverage 20,0%
Automotive T0,5 & T1 48,9%
Automotive Paint shop 23,3%
Automotive Assembly 57,8%
Automotive Logistics 33,3%
Automotive Powertrain 55,6%
Automotive Body in white 42,2%
Automotive Press shop 34,4%
Automotive 80,0%
Agriculture & Forestry 10,0%
Aerospace 41,1%

0,0% 20,0% 40,0% 60,0% 80,0%



5.5 NO. OF ROBOT VISION SYSTEMS INSTALLED - OVERALL

No. of Robot Vision systems installed by the vendors, overall? Only one selection was allowed.
For easier classification the following ranges have been provided to be selected from.

1-5 systems 5-10 systems 10-50 systems
50- 100 systems 100- 500 systems 500+ systems
1000+ systems

Altogether 8 companies claim to have each more than 1000 systems installed.

17 companies have installed more than 100 systems for RV and positioning.

Systems installed for RV and positioning / Overall
9
8
8
7 7
7
6
6
5
4
4
3
2
2
1
1
0
1-5 5-10 10-50 50-100 100-500 500+ 1000+

articles and links.



COPYRIGHT

This market report is authored by AMC Hofmann.

No parts of this report may be reproduced in any manner without prior written
consent of AMC Hofmann. This prohibition includes copying by a firm for its
internal use.

While every attempt has been made to provide accurate information, AMC Hofmann
cannot be held accountable for any omissions or errors.

AMC Hofmann does not ensure the use of such data against liability of any kind.

For more information on this market report please contact AMC Hofmann.

© 2010 by AMC Hofmann

All rights reserved, including the right of translation by AMC Hofmann.

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