.png){kind=icon}
返回
A deep-learning real-time visual SLAM system based on multi-task feature extraction network and self-supervised feature points
.png){kind=icon}
PRE
AI
DOI：10.1016/j.measurement.2020.108403.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Simultaneous Localization and Mapping (SLAM) is the basis for intelligent mobile robots to work in unknown environments. However, traditional feature extraction algorithms that traditional visual SLAM systems rely on have difficulty dealing with texture-less regions and other complex scenes, which limits the development of visual SLAM. The studies of feature points extraction adopting deep learning show that this method has more advantages than traditional methods in dealing with complex scenes, but these studies consider accuracy while ignoring the efficiency. To solve these problems, this paper proposes a deep-learning real-time visual SLAM system based on multi-task feature extraction network and self-supervised feature points. By designing a simplified Convolutional Neural Network (CNN) for detecting feature points and descriptors to replace the traditional feature extractor, the accuracy and stability of the visual SLAM system are enhanced. The experimental results in a dataset and real environments show that the proposed system can maintain high accuracy in a variety of challenging scenes, run on a GPU in real-time, and support the construction of dense 3D maps. Moreover, its overall performance is better than the current traditional visual SLAM system.
Keyword:
Simultaneous localization and mapping (SLAM)
Convolutional neural network (CNN)
Deep learning
Self-supervised feature points
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
5.6
论文数:
2.0W
被引数:
5.4W
机构
引用论文
Carboxylated pillar[n]arene (n= 5–7) host molecules: high affinity and selective binding in water
PREAI
分享收藏AutoMorph: Automated Retinal Vascular Morphology Quantification Via a Deep Learning PipelineAutoMorph: 通过深度学习管道自动量化视网膜血管形态
OAAI
OAAI分享收藏Oral Idarubicin as a Single Agent Therapy in Patients with Relapsed or Resistant Multiple Myeloma
PREAI
分享收藏Conditional simultaneous localization and mapping: A robust visual SLAM system有条件的同时定位和映射: 一个鲁棒的视觉SLAM系统.png)
NEUROCOMPUTING
NEUROCOMPUTINGIF6.5
PREAI
分享收藏Deep EndoVO: A recurrent convolutional neural network (RCNN) based visual odometry approach for endoscopic capsule robotsNEUROCOMPUTING
OAAI
NEUROCOMPUTINGIF6.5
OAAI分享收藏
查看更多内容