CNN stereo vision hardware system for autonomous robot navigation

Sergio Taraglio, Andrea Zanela, Mario Salerno, Fausto Sargeni, Vincenzo Bonaiuto

Research output: Contribution to conferencePaper

3 Citations (Scopus)

Abstract

The high parallel analogue processing rate makes the Cellular Neural Networks paradigm really useful in such a problems where real-time replies to external stimuli are required. The development of an effective system for the autonomous robot navigation can find a valid support from this research. Moreover, the growth of new CNN algorithms can afford the necessary feedback to the hardware developers to improve their realizations. In this paper some measurements of a stereo-vision algorithm on a CNN hardware implementation (the 720DPCNN System) will be shown.
Original languageEnglish
Publication statusPublished - 1998
EventProceedings of the 1998 5th IEEE International Workshop on Cellular Neural Networks and Their Applications, CNNA - , Unknown
Duration: 1 Jan 1998 → …

Conference

ConferenceProceedings of the 1998 5th IEEE International Workshop on Cellular Neural Networks and Their Applications, CNNA
CountryUnknown
Period1/1/98 → …

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All Science Journal Classification (ASJC) codes

  • Software

Cite this

Taraglio, S., Zanela, A., Salerno, M., Sargeni, F., & Bonaiuto, V. (1998). CNN stereo vision hardware system for autonomous robot navigation. Paper presented at Proceedings of the 1998 5th IEEE International Workshop on Cellular Neural Networks and Their Applications, CNNA, Unknown.