Semantic region estimation of assistant robot for the elderly long-term operation in indoor environment
Semantic region estimation of assistant robot for the elderly long-term operation in indoor environment
复制标题
DOI：
10.1109/cc.2016.7489969
复制
发表时间：
2016-05
影响因子：
4.1
通讯作者：
Guanglei Huo;Lijun Zhao;Ke Wang;Ruifeng Li
中科院分区：
文献类型：
--
作者：
Guanglei Huo;Lijun Zhao;Ke Wang;Ruifeng Li
为了提高老年人辅助机器人的空间识别能力，以适应老年人的长期操作任务，提出了一种新的语义区域估计方法。我们定义了一个新的基于图的语义区域描述，这是在一个动态的方式估计。我们提出了一个两级更新算法，即符号更新级和区域更新级。该算法首先采用粒子滤波器更新符号的权值，然后根据权值使用Viterbi算法对机器人所在区域进行最优估计。实验结果表明，我们提出的方法可以解决问题的长期操作和绑架机器人问题。
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.