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The MVP sensor planning system for robotic vision tasks

Konstantinos Tarabanis; Roger Y. Tsai; Peter K. Allen

Title:
The MVP sensor planning system for robotic vision tasks
Author(s):
Tarabanis, Konstantinos
Tsai, Roger Y.
Allen, Peter K.
Date:
Type:
Articles
Department:
Computer Science
Volume:
11
Permanent URL:
Book/Journal Title:
IEEE Transactions on Robotics and Automation
Abstract:
The MVP (machine vision planner) model-based sensor planning system for robotic vision is presented. MVP automatically synthesizes desirable camera views of a scene based on geometric models of the environment, optical models of the vision sensors, and models of the task to be achieved. The generic task of feature detectability has been chosen since it is applicable to many robot-controlled vision systems. For such a task, features of interest in the environment are required to simultaneously be visible, inside the field of view, in focus, and magnified as required. In this paper, we present a technique that poses the vision sensor planning problem in an optimization setting and determines viewpoints that satisfy all previous requirements simultaneously and with a margin. In addition, we present experimental results of this technique when applied to a robotic vision system that consists of a camera mounted on a robot manipulator in a hand-eye configuration.
Subject(s):
Robotics
Publisher DOI:
http://dx.doi.org/10.1109/70.345939
Item views:
108
Metadata:
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