Movement persuit control of an offshore automated platform via a RAM-based neural network

Horácio L. França, João Carlos P. Da Silva, Massimo De Gregorio, Omar Lengerke, Max S. Dutra, Felipe M.G. França

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Scopus citations

Abstract

The reproduction of the movements of a ship by automated platforms, without the use of sensors providing exact data related to the numeric variables involved, is a non-trivial matter. The creation of an artificial vision system that can follow the cadence of said ship, in six axes of freedom, is the goal of this research. Considering that a real time response is a requisite in this case, it was decided to adopt a Boolean artificial neural network system that could identify and follow arbitrary interest points that could define, as a group, a model of the movement of an observed vessel. This paper describes the development of a prototype based on the Boolean perceptron model WiSARD (Wilkie, Stonham and Aleksander's Recognition Device), that is being implemented in the C programming language on a desktop computer using a regular webcam as input.

Original languageEnglish
Title of host publication11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010
Pages2437-2441
Number of pages5
DOIs
StatePublished - 2010
Event11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010 - Singapore, Singapore
Duration: 7 Dec 201010 Dec 2010

Publication series

Name11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010

Conference

Conference11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010
Country/TerritorySingapore
CitySingapore
Period7/12/1010/12/10

Keywords

  • Stewart platform
  • Weightless neural networks
  • WiSARD

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