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Semantic region estimation of assistant robot for the elderly long-term operation in indoor environment

机译:室内环境下老年人长期作业辅助机器人的语义区域估计

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摘要

In this work, in order to improve spatial recognition abilities for the long-term operation tasks of the assistant robot for the elderly, a novel approach of semantic region estimation is proposed. We define a novel graph-based semantic region descriptions, which are estimated in a dynamically fashion. We propose a two-level update algorithm, namely, Symbols update level and Regions update level. The algorithm firstly adopts particle filter to update weights of the symbols, and then use the Viterbi algorithm to estimate the region the robot stays in based on those weights, optimally. Experimental results demonstrate that our proposed approach can solve problems of the long-term operation and kidnapped robot problem.
机译:在这项工作中,为了提高老年人辅助机器人的长期操作任务的空间识别能力,提出了一种新的语义区域估计方法。我们定义了一种新颖的基于图的语义区域描述,该描述以动态方式估算。我们提出了两级更新算法,即符号更新级别和区域更新级别。该算法首先采用粒子滤波来更新符号的权重,然后使用维特比算法基于这些权重来最佳估计机器人停留的区域。实验结果表明,本文提出的方法可以解决长期运行和绑架机器人的问题。

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