关键词: 移动机器人定位, 第一人称视角, 时间序列图像, 递归卷积神经网络, 双轮机器人

Abstract: Mobile robot localization has been considered to be an important task in the ?eld of robotics research. This paper proposes Recurrent Convolutional Neural Networks-Based Mobile Robot Localization（RCNN-MRL） algorithm. RCNN（Recurrent Convolutional Neural Networks） is a neural networks model that combines Convolutional Neural Networks（CNN） and Recurrent Neural Networks（RNN）, and RCNN-MRL estimates the self-position from the first person view captured by a camera on a robot by using RCNN. Specifically, it uses a regression model for localization by using RCNN capable of processing consecutive images. This paper uses simulated environments where a two-wheel robot moves randomly, and analyzes the performance of localization. The experiments show that RCNN model can estimate the self-position of the robot.

Key words: mobile robot localization, first person view, time series image, convolutional neural networks, two-wheel robot