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Neural network-based autonomous navigation for a homecare mobile robot

机译:基于神经网络的家庭护理移动机器人自主导航

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By the number of people aged 60 or over and people with disabilities growing, homecare mobile robot draws increasing attention. However, there are challenges of autonomous navigation for homecare robot such as frequent changes of environment, obstacles and goal position. In this paper, we focus on verifying potential of neural network-based autonomous navigation for homecare mobile. And we compare recurrent neural network with multilayer perceptron in the navigation of an autonomous mobile robot. The result suggested that the recurrent neural network can do better robot navigation because of its capability to handle the temporal dependency of a data sequence. Also, it shows that neural network-based navigation can be a good alternative since it has decent generalization ability for new environment, obstacles and goals.
机译:随着60岁以上的老年人和残疾人的增多,家庭护理移动机器人吸引了越来越多的关注。但是,对于家庭护理机器人来说,自主导航存在挑战,例如环境,障碍物和目标位置的频繁变化。在本文中,我们专注于验证基于神经网络的自主导航在家庭护理手机中的潜力。而且,我们在自主移动机器人的导航中将递归神经网络与多层感知器进行了比较。结果表明,由于递归神经网络能够处理数据序列的时间依赖性,因此可以更好地进行机器人导航。而且,它表明基于神经网络的导航可以很好地替代,因为它对新环境,障碍和目标具有不错的概括能力。

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