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Distributed visual navigation based on neural Q-learning for a mobile robot

机译:基于神经Q学习的移动机器人分布式视觉导航

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摘要

Distributed visual navigation based on neural Q-learning for a mobile robot is studied in this paper. First, a general distributed structure based on the multiple processors for visual navigation is established according to the decomposition of the mobile robot visual navigation task. Second, in terms of the general distributed structure, the local environment description method based on the Peer Group Filtering (PGF) and fuzzy technology is put forward. Third, in each local environment description, a controller based on neural Q-learning is designed to guide the mobile robot navigation. In the last part of this paper, experimental simulations are done to test the effectiveness of the presented distributed algorithm, including the image segmentation, environment description and navigation policy.
机译:本文研究了基于神经Q学习的移动机器人分布式视觉导航。首先,根据移动机器人视觉导航任务的分解,建立了基于多个处理器的视觉导航通用分布式结构。其次,针对一般的分布式结构,提出了基于对等组过滤和模糊技术的局部环境描述方法。第三,在每个局部环境描述中,基于神经Q学习的控制器被设计为引导移动机器人导航。在本文的最后一部分,通过实验仿真来测试所提出的分布式算法的有效性,包括图像分割,环境描述和导航策略。

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