Open Access

Using High-Level RTOS Models for HW/SW Embedded Architecture Exploration: Case Study on Mobile Robotic Vision

  • François Verdier1Email author,
  • Benoît Miramond1,
  • Mickaël Maillard1,
  • Emmanuel Huck1 and
  • Thomas Lefebvre1
EURASIP Journal on Embedded Systems20082008:349465

DOI: 10.1155/2008/349465

Received: 1 March 2008

Accepted: 22 July 2008

Published: 4 August 2008

Abstract

We are interested in the design of a system-on-chip implementing the vision system of a mobile robot. Following a biologically inspired approach, this vision architecture belongs to a larger sensorimotor loop. This regulation loop both creates and exploits dynamics properties to achieve a wide variety of target tracking and navigation objectives. Such a system is representative of numerous flexible and dynamic applications which are more and more encountered in embedded systems. In order to deal with all of the dynamic aspects of these applications, it appears necessary to embed a dedicated real-time operating system on the chip. The presence of this on-chip custom executive layer constitutes a major scientific obstacle in the traditional hardware and software design flows. Classical exploration and simulation tools are particularly inappropriate in this case. We detail in this paper the specific mechanisms necessary to build a high-level model of an embedded custom operating system able to manage such a real-time but flexible application. We also describe our executable RTOS model written in SystemC allowing an early simulation of our application on top of its specific scheduling layer. Based on this model, a methodology is discussed and results are given on the exploration and validation of a distributed platform adapted to this vision system.

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Authors’ Affiliations

(1)
ETIS Laboratory, CNRS UMR 8051/University of Cergy-Pontoise/ENSEA

Copyright

© Francois Verdier et al. 2008

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.