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An AAL scenario involving automatic data collection and robotic manipulation

机译:涉及自动数据收集和机器人操作的AAL场景

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In this paper, we describe an Ambient Assisted Living (AAL) scenario which includes a robotic platform employed in automatic data collection and assistance. As part of this scenario we propose new algorithms and solutions for indoor localization and manipulation. The former involves automatic data collection of WLAN RSS fingerprints by the robotic platform. The latter involves object manipulation with focus on grasping algorithms. Our new hybrid approach, where the localization problem is split into two stages, which are modelled as a classification and regression problem, proves to deliver the best positioning accuracy even when compared with deterministic approaches. At the same time, we also obtained improved results in the object grasping approach. The improvement is most pronounced for previously unseen data showing that our method is able to better generalize new environments.
机译:在本文中,我们描述了一个环境辅助生活(AAL)场景,包括在自动数据收集和辅助中使用的机器人平台。作为这一情景的一部分,我们提出了新的算法和用于室内定位和操纵的解决方案。前者涉及机器人平台自动数据收集WLAN RSS指纹。后者涉及对象操纵,重点是掌握算法。我们的新混合方法,其中定位问题被分成两个阶段,这些阶段被建模为分类和回归问题,证明即使与确定性方法相比,也能够提供最佳定位精度。与此同时,我们还获得了对象抓取方法的改善结果。对于先前的未见数据,该改进最为明显,显示我们的方法能够更好地概括新环境。

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