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  4. Enabling Neural Network Edge Computing on a Small Robot Vehicle
 
Verlagslink DOI
10.1007/978-3-031-29104-3_4

Enabling Neural Network Edge Computing on a Small Robot Vehicle

Veröffentlichungsdatum
2023
Autoren
Bredereke, Jan  
Zusammenfassung
We report on experiences with optimizations that enable neural network edge computing on a small robot vehicle, which serves as a proxy for an autonomous robotic space craft. We realize a visual object recognition task using a neural network on a field-programmable gate array (FPGA) with data processing resources as limited as those of an FPGA suitable for space. We use a quantized neural network nicely matching the properties of an FPGA. The restrictions of the small FPGA require us to sequentialize the processing partially. We employ input frame tiling for this. It allows us to keep the entire neural network on-chip. Furthermore, we split up the visual object recognition task into two stages, using two separate neural networks. The first stage identifies the region of interest approximately, using large and thus few tiles. The second stage looks closely at the single tile containing the region of interest; thus being not that time critical.
Verlag
Springer International Publishing
Institution
Hochschule Bremen  
Fachbereich
Hochschule Bremen - Fakultät 4: Elektrotechnik und Informatik  
Dokumenttyp
Artikel/Aufsatz
Zeitschrift/Sammelwerk
Intelligent Distributed Computing XV  
Serie(s)
Studies in Computational Intelligence  
Startseite
33
Endseite
40
Sprache
Englisch

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