Flexible Composition of Robot Logic with Computer Vision Services
Doktorsavhandling, 2018

Vision-based robotics is an ever-growing field within industrial automation. Demands for greater flexibility and higher quality motivate manufacturing companies to adopt these technologies for such tasks as material handling, assembly, and inspection. In addition to the direct use in the manufacturing setting, robots combined with vision systems serve as highly flexible means for realization of prototyping test-beds in the R&D context.

Traditionally, the problem areas of robotics and computer vision are attacked separately. An exception is the study of vision-based servo control, the focus of which constitutes control-theoretic aspects of vision-based robot guidance under assumption that robot joints can be controlled directly. The missing part is a systemic approach to implementing robotic application with vision sensing given industrial robots constrained by their programming interface.

This thesis targets the development process of vision-based robotic systems in an event-driven environment. It focuses on design and composition of three functional components: (1) robot control function, (2) image acquisition function, and (3) image processing function. The thesis approaches its goal by a combination of laboratory results, a case study of an industrial company (Kongsberg Automotive AS), and formalization of computational abstractions and architectural solutions.

The image processing function is tackled with the application of reactive pipelines. The proposed system development method allows for smooth transition from early-stage vision algorithm prototyping to the integration phase. The image acquisition function in this thesis is exposed in a service-oriented manner with the help of a flexible set of concurrent computational primitives. To realize control of industrial robots, a distributed architecture is devised, which supports composability of communication-heavy robot logic, as well as flexible coupling of the robot control node with vision services.


data flow

service-oriented architecture

distributed systems

machine learning

discrete-event systems

Machine vision


Room ED, Hörsalsvägen 11, Campus Johanneberg
Opponent: Prof. Robert Harrison, The University of Warwick


Oleksandr Semeniuta

Chalmers, Elektroteknik, System- och reglerteknik, Automation

Oleksandr Semeniuta, Sebastian Dransfeld, Kristian Martinsen, and Petter Falkman. Towards increased intelligence and automatic improvement in industrial vision systems. Procedia CIRP, 67:256–261, 2018. ISSN 22128271. doi: 10.1016/j.procir.2017.12.209

Oleksandr Semeniuta, Sebastian Dransfeld, and Petter Falkman. Visionbased robotic system for picking and inspection of small automotive components. In 2016 IEEE International Conference on Automation Science and Engineering (CASE), pages 549–554. IEEE, aug 2016. ISBN 978-1-5090-2409- 4. doi: 10.1109/COASE.2016.7743452

Oleksandr Semeniuta and Petter Falkman. EPypes: a framework for building event-driven data processing pipelines. Submitted to: PeerJ Computer Science

Oleksandr Semeniuta and Petter Falkman. Flexible image acquisition service for distributed robotic systems. In 2018 Second IEEE International Conference on Robotic Computing (IRC), pages 106–112. IEEE, jan 2018. ISBN 978-1-5386-4652-6. doi: 10.1109/IRC.2018.00024

Oleksandr Semeniuta and Petter Falkman. Event-driven industrial robot control architecture for the Adept V+ platform. Submitted to: Frontiers in Robotics and AI


Informations- och kommunikationsteknik




Robotteknik och automation

Datavetenskap (datalogi)




Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4458


Chalmers tekniska högskola

Room ED, Hörsalsvägen 11, Campus Johanneberg

Opponent: Prof. Robert Harrison, The University of Warwick

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