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Mathias Hauan Arbo about his PhD

2/11/2020

 
Mathias Hauan Arbo was one of the first PhD candidates of SFI Manufacturing. In april 2019 he finished his thesis on "Robotic assembly and optimization-based control of industrial manipulators". We asked him to tell us a bit more about his research. 

– My thesis has two main topics: An idealized automatic assembly system, capable of generating and executing robot programs based on CAD models, and closed-loop inverse kinematics systems for on-line control of an industrial manipulator, explains Mathias.

The thesis is a collection of papers related to these topics written during Mathias’ work at SFI Manufacturing. The accompanying text in the thesis gives a brief introduction to the history of robotics, as well as an overview of some of the robotics literature.

Mathias started his SFI Manufacturing Postdoc Spring 2019​. During his Postdoc he will be working on high-level planning and control of articulated robots for assembly, exploiting expert knowledge and CAD information. 
​
Read Mathias his thesis here

Find the presentation of the defendence (and video) here

Potential economic impact of SFI Manufacturing: >3 billion NOK/year

12/9/2019

 
An independent report shows that SFI Manufacturing potentially can have an economic impact of >3 billion NOK per year in the Norwegian manufacturing industry.

SFI Manufacturing is a cross-disciplinary centre for research-based innovation for competitive high value manufacturing in Norway. The centre is hosted by SINTEF Manufacturing AS, it has 14 industry partners, and SINTEF and NTNU as research partner. An analysis of the independent advisory firm Impello Management AS shows that the centre potentially can have an economic impact of >3 billion NOK per year in the Norwegian manufacturing industry.

SFI Manufacturing has been awarded 30 IPN projects in the period of 2016-2019. The analysis of Impello Management AS is based on 15 of these projects started in 2018, and statements of the industry partners in relation to these projects. To realize the potential economic impact, significant investments from the industry will be required.

More potential impact
The analysis shows more potential economic impacts in addition to the 3 billion NOK as well: Reduced operating costs, increased profits and reduced investments. These impacts are based on 8 use cases linked to the 15 IPN projects. The use cases are subsequently linked to one or more of the centre's research areas: Multi-material products and processes, Flexible and robust automation, and Sustainable and innovative organizations.

Specifically, the 8 use cases are covering the fields of:
  • New joining methods for high-performance aluminum-steel products
  • Additive manufacturing of elastomer products
  • Robust robotic motion planning for manufacturing
  • Software architecture and tools for «batch size one» robotic assembly
  • 3D vision: Deep learning for robotic grasping
  • Benchmarking enterprise development maturity
  • Modernization of vocational education and training
  • Alignment of management tools

It is in these fields where the potential economic impact of SFI Manufacturing lies.

Key facts about SFI Manufacturing
  • Centre for research-based innovation (2015-2022) hosted by SINTEF Manufacturing AS, which has its main basis at Raufoss Industry Park, Oppland.
  • Industry partners: Benteler Automotive, Brødrene Aa, Ekornes, GKN Aerospace Norway, Hexagon Raufoss, HyBond, Hydro, Kongsberg Automotive, Mjøs Metallvarefabrikk, Nammo, Neuman Aluminium, Plasto, Rolls-Royce, Sandvik Teeness.
  • Research partners: SINTEF, NTNU.
  • Research areas: Multi-material products and processes, Flexible and robust automation, Sustainable and innovative organizations.
  • Turnover: The budget for 2015-2022 is 202 MNOK. In addition, the centre has been awarded 30 IPN projects in the period of 2016-2019, with a total value of 850 MNOK.
  • PhD, Postdoc and Masters (31.10.2019): PhD: 1 finished + 12 ongoing + 3 planned, Postdoc: 2 ongoing + 2 planned, Masters: 25 completed + 75 planned.
  • Scientific publications (09.12.2019): >85

Contact person
  • Sverre Gulbrandsen-Dahl, Centre Manager of SFI Manufacturing. Email: sverre.gulbrandsen-dahl@sintef.no, phone number: +47 916 01 205.
    ​
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Automated production line at Plasto AS, a leading company in the injection molding industry, and one of the industry partners of SFI Manufacturing. Photo: Plasto AS

Conference on advanced manufacturing and automation

11/25/2019

 
SFI Manufacturing joined IWAMA 2019, an international conference for academic and industrial experts in the field of advanced manufacturing and automation.

On the 21st and 22nd of November, the 9th edition of IWAMA took place in the United Kingdom, at the Plymouth University. Researchers of SFI Manufacturing travelled to Plymouth to join the conference.

IWAMA – International Workshop of Advanced Manufacturing and Automation – is an important international conference on advanced manufacturing and automation, and takes place in China or the United Kingdom every year.

Manufacturing and automation has assumed paramount importance and are vital factors for the maintenance and improvement of the economy of a nation and the quality of life. The field of manufacturing and automation is advancing at a rapid pace and new technologies are also emerging in the field. The challenges faced by today’s engineers are forcing them to keep on top of the emerging trends through continuous research and development.

​IWAMA aims at providing a common platform for academics, researchers, practicing professionals and experts from industries to interact and discuss trends and advances in some areas of manufacturing and automation, while sharing ideas and perspectives.

Tone Gjerstad and Gabor Sziebig joined as researchers from SFI Manufacturing – Research Area 2. Many other colleagues from SINTEF joined as well, such as Eirin Lodgaard, Ragnhild Eleftheriadis, Davar Hemyari and Even Wilberg Hovig, who contributed with presentations on the latest proceedings in the scientific field of advanced manufacturing and automation.

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Researcher Gabor Sziebig about high-payload human-robot collaboration, and communication based on sensor fusion. Photo: SFI Manufacturing

Signe Moe about herĀ postdoc at SFI Manufacturing

8/23/2017

 
Hi, my name is Signe Moe and I am a postdoctoral fellow at SFI Manufacturing, where I hope that several of my competences acquired during my PhD can be put to good use to ensure more effective production.
 
I graduated with a master’s degree in cybernetics in 2013 and immediately continued on a PhD at NTNU AMOS, Center for Autonomous Marine Operations and Systems, and in 2016 I completed my thesis “Guidance and Control of Robot Manipulators and Autonomous Marine Robots”. Soon thereafter I was officially a part of the SFI Manufacturing researcher team.
 
Set-based control of robotic systems
One of the main contributions of my PhD was the development of a control framework for robotic systems allowing us to define and control set-based tasks. Instead of telling a robot exactly what to do, we define a valid interval of states and ensure that our robot stays within these limits. This results in a system with more option on to perform its tasks, and opens up for a more efficient control structure. Furthermore, the framework is completely general and may therefore be applied to numerous applications.
 
Manufacturing
One possible task that is highly relevant for manufacturing purposes is directional control of robots, something which may be used to decrease operation time and/or energy consumption for instance in autonomous spray painting, welding and cleaning operations.
 
Another highly relevant task for any robotic system is collision avoidance, which is crucial to ensure safe and efficient operations. The set-based control framework may also be applied to this end, where the valid interval of the set-based task is defined as the set of safe distances between the robot and any obstacle.
 
Co-supervising
As part of my postdoctoral fellowship I am a co-supervisor to PhD-candidate Linn Danielsen Evjemo, who will work on 3D-printing by the use of robots. This will enable printing of larger objects in a much more versatile manner, as 3D-printing is currently performed in closed chambers in a strictly layer wise, horizontal routine. Robotic manipulators have a larger range and several additional degrees of freedom with regards to orientation control. Together, Linn and I have run initial, small-scale experiments as a proof of concept, where we used a small manipulator and a caulking gun to print a small cup.
​
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A Tuesday in the life of PhD candidate Mathias

6/1/2016

 
Mathias Hauan Arbo's PhD started in the fall of 2015 and focuses on robotic assembly and sensor fusion. Below Mathias will describe a Tuesday in his life as PhD candidate in SFI Manufacturing.

Shower. Breakfast. Brisk walk. Card, key, computer. And finally the much wanted cup of coffee. Tuesday mornings are the beginning of the work week that Monday wasn’t, as I usually try to let Mondays have emails and administrative tasks. After a brief coffee deliberation with my officemates, an email ticks in from IEEE. Every Tuesday morning, I get an update on last weeks published papers on industrial robotics and force control.

Not all are relevant, nor are all good, but sometimes an interesting paper comes along that shines through. And as I haven’t been doing research for long, it is important to try to establish an overview of the field, and where the good work is done. The next hour I go through the articles, saving those of interest and adding them to my Mendeley archive with short keywords so that they can be easily found later if needed.

Courses at NTNU
This semester I had 2 PhD courses and a self-study course. The two courses I had were TK8103: Advanced Nonlinear Systems and TK8102: Nonlinear State Estimation. In both courses we were to write a conference article. This semester essentially became a crash-course in academic writing and working.

In TK8102 I looked at the stability of a recently developed speed observer and a classic trajectory tracking controller for a robot. And in TK8103 I compared the previous observer-controller system to a “dynamic” trajectory tracking controller. We recently completed our presentations for the subjects, and got feedback as to what should be fixed. And I start working on that.
 
I get a tap on the shoulder “Lunch?”, the sun is shining and the weather is nice, we gather our troops and pass by the cafeteria to pick up some food before sitting outside in the sunshine. After a while we return to work and I continue where I left off. A typical Tuesday is reading, writing, coding and debugging. With some coffee and lunch breaks sprinkled on top.

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Second PhD student of SFI Manufacturing

10/6/2015

 
Hi, my name is Mathias Hauan Arbo and I am the second PhD student that will be working with SFI Manufacturing. The Bayesian approach to robotics is what I will employ in my PhD. 

I come from the department of engineering cybernetics and work mainly with sensor fusion and robotics. My master thesis was on sensor fusion of delayed displacement measurements. The Bayesian formulation of how to handle that delay was my main topic. Describing the general underlying probability based algorithm for handling delayed displacement measurements in systems doing localization. This Bayesian approach to robotics is what I will employ in my PhD. I will be focusing on using a sensor fusion approach to robots interacting with flexible materials and objects. 

Robots and manufacturing processes
​Rigid-body physics allows us to create highly accurate models for the motion of objects that obey the rigid-body assumptions. And with modern techniques for grasping, computer vision, and sensor fusion, industrial robots are used in a variety of manufacturing processes.
 
Unfortunately, most objects do not always obey those rules. Metals bend, cloth folds, and wood breaks. This means that one either has to rely on human workers, or dedicated tools and hardware for each task. This limits a robot’s adaptability, and subsequently limits the industry.
 
Yet, mechanically, a robot should be capable of doing anything a human can do. To grasp an object so as to minimize the strain it will feel when moved is a matter of accurate modeling and planning. To move an object without it bending is a matter of sensor fusion with assumptions on flexibility. And to do this in an environment for manufacturing requires the combination of these things.

Robots interacting with flexible materials
The focus in this PhD will be on robots interacting with flexible materials. More specifically on how to use sensor fusion methods for tracking flexible objects, grasping strategies, and manipulation of flexible materials with industrial robots.
 
A probabilistic approach to tracking and localization of a robot manipulator when interacting with flexible materials may allow us to handle unmodeled vibrations and flexing as positional uncertainties. This may be useful for path planning, and ensuring safety in human-robot interactions. Right now, the goal is only a faint shimmer in the distance. And it is time to start figuring out the lay of the land, so that I can find the best path there.
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