A Fuzzy Approach for Vision-Based Object Perception in Robot Telecontrol

Chensheng Wang, Fei Wang, Xiaochun Wang, J. Vergeest, T. Wiegers
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Abstract

For human being the object perception process is often conducted in a non-crisp manner, in which vagueness plays one of the pivot roles. In this paper, we propose a Fuzzy logic based approach for vision-based object perception in enhanced reality, supported by a shape repository. By means of defining the Fuzzy matching and reasoning rules, the proposed approach is capable of supporting the Fuzzy decision making process in finding the matching shape model in the repository. Experiment results confirm that the proposed method is both valid and effective in the designated application.
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机器人遥控中基于视觉的物体感知模糊方法
对于人类来说,物体的感知过程往往是不清晰的,其中模糊性起着举足轻重的作用。在本文中,我们提出了一种基于模糊逻辑的增强现实中基于视觉的物体感知方法,该方法由形状存储库支持。通过定义模糊匹配和推理规则,该方法能够支持在存储库中寻找匹配形状模型的模糊决策过程。实验结果表明,该方法在指定的应用中是有效的。
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