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.
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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。
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