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MANIPULATION

Hardware Implementation of a Neural-Network Recognition Module for Visual Servoing in a Mobile Robot

Maria Isabel de la Fuente, Javier Echanobe, I. del Campo, Loreto Susperregui, Iñaki Maurtua

Year
2010
Citations
5

Abstract

This paper describes the initial steps in the development of an object detection system for manipulation purposes, to be embedded in a mobile robot. The goal is to design a robotic system to aid workers in a manufacturing plant. The proposed implementation involves the integration of a Field Programmable Gate Array (FPGA) based electronic module with the manipulator arm of the robotic platform. The whole system is provided with a camera which captures images of the objects that can be found in the environment. The FPGA performs the object recognition tasks by means of a neural network. Additional image processing algorithms are used to convert the images obtained by the camera into useful information for the neural network.

Keywords

Field-programmable gate arrayComputer scienceVisual servoingArtificial neural networkMobile robotArtificial intelligenceComputer visionRobotObject (grammar)Object detection

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