Reconfigurable pipelined sensing for image-based control

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Abstract

Image-based control systems are becoming common in domains such as robotics, healthcare and industrial automation. Coping with a long sample period because of the latency of the image processing algorithm is an open challenge. Modern multi-core platforms allow to address this challenge by pipelining the sensing algorithm. Often, such systems share the resources with other tasks. We show that the performance of an image-based controller can be improved by pipelining the image processing algorithm on unallocated cores. It can be further improved by dynamically allocating (i.e. reconfiguring) cores that are temporarily not used by other tasks to the sensing pipeline. We present a state-based modelling strategy for pipelined and reconfigurable pipelined sensing. We introduce a control design strategy for reconfigurable pipelined systems that assures stability and shows improvement in the control performance.
Original languageEnglish
Title of host publication2016 11th IEEE International Symposium on Industrial Embedded Systems (SIES), Krakow, Poland, 23-25 May 2016 : Proceedings
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Number of pages8
ISBN (Print)978-1-5090-2282-3
DOIs
Publication statusPublished - 2016
Event11th IEEE International Symposium on Industrial Embedded Systems (SIES 2016), May 23-25, 2016, Krakow, Poland - Krakow, Poland
Duration: 23 May 201625 May 2016
http://sies2016.org/

Conference

Conference11th IEEE International Symposium on Industrial Embedded Systems (SIES 2016), May 23-25, 2016, Krakow, Poland
Abbreviated titleSIES 2016
CountryPoland
CityKrakow
Period23/05/1625/05/16
Internet address

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Cite this

Medina , R., Stuijk, S., Goswami, D., & Basten, T. (2016). Reconfigurable pipelined sensing for image-based control. In 2016 11th IEEE International Symposium on Industrial Embedded Systems (SIES), Krakow, Poland, 23-25 May 2016 : Proceedings Piscataway: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/SIES.2016.7509406