Exploring Underwater Environments with Curiosity

Yogesh A. Girdhar, G. Dudek
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引用次数: 18

Abstract

This paper presents a novel approach to modeling curiosity in a mobile robot, which is useful for monitoring and adaptive data collection tasks. We use ROST, a real time topic modeling framework to build a semantic perception model of the environment, using which, we plan a path through the locations in the world with high semantic information content. We demonstrate the approach using the Aqua robot in a variety of different scenarios, and find the robot be able to do tasks such as coral reef inspection, diver following, and sea floor exploration, without any prior training or preparation.
带着好奇心探索水下环境
本文提出了一种新的移动机器人好奇心建模方法,该方法可用于监测和自适应数据收集任务。我们使用实时主题建模框架ROST建立了环境的语义感知模型,利用该模型,我们在世界上具有高语义信息含量的位置规划路径。我们在各种不同的场景中使用Aqua机器人演示了这种方法,并发现机器人能够完成诸如珊瑚礁检查,潜水员跟随和海底勘探等任务,而无需任何事先的培训或准备。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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