Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A Step Towards the Design of Collaborative Autonomous Machines: A Study on Construction and Mining Equipment
Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.ORCID iD: 0000-0002-7741-6405
2019 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Fully autonomous construction and mining machines are not science fiction anymore. For special applications, these types of machinery are well known for several years. The construction and mining industries are ripe for innovative product and service offers, including automated and fully autonomous machines at a larger scale. Nevertheless, commercially available autonomous machines for the main markets are still rare. Driven by the advancements in sensor technology, increased connectivity, and on-board computational capabilities, automation of machine functions and subsystems led to the development of advanced operator-assistant functions in certain fields like material handling, predictive maintenance, and operator guidance. Semi-automated machines, supporting the machine operator during normal operation, are well accepted by users and customers and show beneficial effects on the productivity of the machine and the overall work process. The purpose of this thesis is to generate a deeper understanding of the specific requirements needed to support the design decisions during the development of fully autonomous machines. Complementary, deeper insights into the efficient collaboration between autonomous machines and human collaborators are explored.

The thesis summarizes the research performed by the author, as an industrial Ph.D. student and Specialist for Intelligent Machines at Volvo Construction Equipment. Performed research comprises the investigation of the state-of-the-art approaches in the automation of machines and dedicated functions with special emphasis on the connectivity of the different systems and components up to the site management solution. Further, the work includes the exploration of data-mining through early experience prototyping as a step towards data-driven design of a product-service system. In additional the research covered the support of on-site collaboration between autonomous machines and humans by investigating team behavior and trust development among humans.

Conclusions from this work are that autonomous machine design requires new sets of requirements to support early decision making during the development process. Dedicated data collection based on different methods such as, data-mining, needfinding, and observations, supported by multiple physical and virtual artifacts can generate useful data to support the decision-making. Trust between humans and machines, and the preconditions of developing this trust need to be captured as specific requirements. To support further development in the area of autonomous machine design, an interaction model had been proposed to map possible interactions of an autonomous machine with objects and collaborators within the same work area. To capture the different nature of the possible interactions, several levels had been introduced to enable the distinction between cognitive, and physical, as well as intended, and unintended interactions.

 

Place, publisher, year, edition, pages
Karlskrona: Blekinge Tekniska Högskola, 2019.
Series
Blekinge Institute of Technology Licentiate Dissertation Series, ISSN 1650-2140 ; 17
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:bth-18944ISBN: 978-91-7295-393-2 (print)OAI: oai:DiVA.org:bth-18944DiVA, id: diva2:1371956
Presentation
2019-12-19, J1650, Campus Gräsvik, Karlskrona, 15:00 (English)
Opponent
Supervisors
Available from: 2019-11-21 Created: 2019-11-21 Last updated: 2019-12-18Bibliographically approved
List of papers
1. Connected Machinery - Enabling Automation
Open this publication in new window or tab >>Connected Machinery - Enabling Automation
2015 (English)In: 8th AVL International Commercial Powertrain Conference Proceedings (2015) / [ed] AVL List GmbH, SAE International, Graz, Austria: Society of Automotive Engineers, 2015, Vol. 8, p. 91-95, article id 4.3Conference paper, Published paper (Refereed)
Abstract [en]

With the increased demand on fuel efficiency andproductivity of the different construction equipmenttypes, the connection of the equipment’s subsystems, the connection between the different on sitemachines and the connection to the site managementgets more and more important. By analyzing thedifferent systems and the underlying requirements,several optimization possibilities arise with theconnection of the different data sources. It will beshown that the connection of the different system onmachine level as well as the connection betweenmachines will have a big impact on performance andefficiency of the systems and subsequently of themachine itself.

Place, publisher, year, edition, pages
Graz, Austria: Society of Automotive Engineers, 2015
Series
AVL International Commercial Powertrain Conference Proceedings ; 8 (2015)
Keywords
Connectivity, Automation, Non-road mobile machinery, Mining
National Category
Other Mechanical Engineering
Identifiers
urn:nbn:se:bth-18973 (URN)
Conference
8th AVL International Commercial Powertrain Conference, Graz
Available from: 2019-11-28 Created: 2019-11-28 Last updated: 2019-12-03Bibliographically approved
2. Data Mining through Early Experience Prototyping: A step towards Data Driven Product Service System Design
Open this publication in new window or tab >>Data Mining through Early Experience Prototyping: A step towards Data Driven Product Service System Design
2018 (English)In: IFAC PAPERSONLINE, Elsevier, 2018, Vol. 51, no 11, p. 1095-1100, article id 11Conference paper, Published paper (Refereed)
Abstract [en]

The construction industry is ripe for disruption through innovative solutions that provide added productivity. Equipment manufacturers are attempting to disrupt their industry with investments in autonomy, electrification and product-service system business models. Designing solutions that will operate in completely new systems or modify an existing complex system require new approaches to address the uncertainty of system impacts. An iterative approach can help tackle ambiguity through cyclical validation of design decisions. Data mining in each cycle adds a quantitative dimension to the rationale of decision making, but data is sparse and difficult to collect in parallel with design of theoretical product-service systems operating in future scenarios. This can be combated using experiential prototyping techniques to design flexible infrastructure that supports contextualized data gathering in a variety of focused design sprints using Design, Build and Test approach. The intricacy of designing innovative solutions to increase productivity in the construction industry can be untangled by framing aspects of the problem in small sprints and testing them in a contextualized setting built to generate functional data to drive design.

Place, publisher, year, edition, pages
Elsevier, 2018
Series
IFAC PAPERSONLINE, ISSN 2405-8963 ; 51
Keywords
​Product Service System, Data Mining, Experience Prototyping, New Machine Development
National Category
Other Mechanical Engineering
Identifiers
urn:nbn:se:bth-16395 (URN)10.1016/j.ifacol.2018.08.458 (DOI)000445651000183 ()
Conference
16th IFAC Symposium on Information Control Problems in Manufacturing, Bergamo
Projects
Model Driven Development and Decision Support
Funder
Knowledge Foundation, 20120278
Available from: 2018-06-11 Created: 2018-06-11 Last updated: 2019-12-03Bibliographically approved
3. Towards Autonomous Construction Equipment: Supporting On-Site Collaboration Between Automatons and Humans
Open this publication in new window or tab >>Towards Autonomous Construction Equipment: Supporting On-Site Collaboration Between Automatons and Humans
(English)In: International Journal of Product Development, ISSN 1477-9056, E-ISSN 1741-8178Article in journal (Refereed) Accepted
Abstract [en]

To support the application of automated machines andcollaborative robots in unstructured environments like in the mining,agriculture and construction sector the needs of the human co-workershould be investigated to ensure a safe and productive collaboration.The empirical study presented includes the prototyping of a solution forhuman-machine communication, which has been supported by a designthinking approach. An understanding of the human needs had beencreated through jobsite observations and semi-structured interviewswith human workforces working in close proximity to heavy mobileequipment. The results shows that trust and communication have a bigimpact on the jobsite collaboration.

Keywords
Human-Robot Collaboration, Autonomous Machines, Construction Sites, User Experience, Design Thinking, Human-Robot Trust, Human-Robot Teamwork
National Category
Other Mechanical Engineering
Identifiers
urn:nbn:se:bth-18988 (URN)
Projects
Model Driven Development and Decision Support
Available from: 2019-12-03 Created: 2019-12-03 Last updated: 2019-12-13Bibliographically approved

Open Access in DiVA

fulltext(18020 kB)35 downloads
File information
File name FULLTEXT02.pdfFile size 18020 kBChecksum SHA-512
ec4ccac322499d0147e476f99014d4392d93c8413b450e5a02255c2797c36d4c9f30237a1669453e65ef0f012c34d19cd8c42f755949fef0f00d136a00e9f01a
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Frank, Martin
By organisation
Department of Mechanical Engineering
Mechanical Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 79 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 517 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf