计算机与数字工程2019，Vol.47Issue(5)：1020-1026,1048,8.DOI:10.3969/j.issn.1672-9722.2019.05.002
基于卷积神经网络的回环检测算法
Loop Closure Detection Based on Convolutional Neural Network
摘要
Abstract
This paper focuses on the problem of loop closure detection in mobile robots during visual positioning and mapping. Loop closure detection is one of the most important parts of visual SLAM. During the movement of the robot,the robot realizes posi?tioning and mapping by estimating its own posture and sensing the surrounding environment. Since the robot uses the inter-frame pose estimation when estimating the pose,the estimation of the pose is drifted over time. Loop closure detection is aimed at solving the pose drift problem. Nowadays,the more popular method is to use the artificially built features and use the visual word bag meth?od to achieve loopback detection. This paper proposes a loopback detection method based on deep learning for convolutional neural networks. The mobile robot acquires the data of the visual image through the sensor,inputs it into the trained convolutional neural network,uses the convolution feature as the description of the image,and then processes the extracted feature to calculate the simi?larity score of the image. Finally,the validity of the verification algorithm is performed using the local dataset and the TUM dataset.关键词
视觉SLAM/回环检测/深度学习/位姿漂移/卷积神经网络Key words
visual SLAM/loop closure detection/deep learning/pose drift/convolutional neural network分类
信息技术与安全科学引用本文复制引用
罗顺心,张孙杰..基于卷积神经网络的回环检测算法[J].计算机与数字工程,2019,47(5):1020-1026,1048,8.基金项目
国家自然科学基金项目(编号:61603255)资助. （编号:61603255）
