Semantic SLAMHuman-computer interaction requires accurate localization and effective mapping, while dynamic objects can influence the accuracy of localization and mapping. State-of-the-art SLAM algorithms assume
链接:A Survey of Visual SLAM in Dynamic Environment: The Evolution From Geometric to Semantic Approaches | IEEE Journals & Magazine | IEEE Xplore 一、研究动机: 传统的视觉SLAM方法,如ORB-SLAM家族和VINS-Mono,在静态环境中表现出色,但在动态和不可预测的环境中遇到了重大挑战。这篇文章深入研究了SLAM从基...
In the classical SLAM framework, both feature point methods and direct methods rely on the assumption that the environment in which the robot is located is a static one. This assumption limits the application of SLAM algorithms in real environments. When dynamic objects are encountered in real-...
DS-SLAM:通过SegNet与移动一致检测提取语义和移动信息。 Dynamic-SLAM:丰富SSD物体检测模型至语义水平来确定运动物体的形状。 DP SLAM:基于动态关键点的移动概率传播估计,结合极点几何约束和语义分割成贝叶斯滤波器。 DGS-SLAM:使用结合从语义分割得到的可能的运动信息的多项式残差网络来检测动态物体。 ②基于光流网络预估...
Dynamic Environments 语义分割&光流 DS-SLAM:A Semantic Visual SLAM towards Dynamic Environments 语义分割 & 运动一致性检测& octomap 语义概率数据融合 语义slam 博客解析 VSO: Visual Semantic Odometry 语义概率数据融合 知乎论文解析 数学描述 参考 动态场景下基于实例分割的SLAM(毕业设计动态SLAM论文学习部分) 20...
Over the past decades, many impressed SLAM systems have been developed and achieved good performance under certain circumstances. However, some problems are still not well solved, for example, how to tackle the moving objects in the dynamic environments, how to make the robots truly understand the...
To address this issue, a new real-time visual SLAM system called MG-SLAM has been developed. Based on ORB-SLAM2, MG-SLAM incorporates a dynamic target detection process that enables the detection of both known and unknown moving objects. In this process, a separate semantic segmentation thread...
Most current visual SLAM systems rely on static environment assumptions. However, in dynamic environments, the presence of dynamic objects can severely impair the performance of visual SLAM systems. To address this issue, we propose an algorithm that combines semantic segmentation and geometric constraint...
Aiming at the problem of poor autonomous adaptability of mobile robots to dynamic environments, this paper propose a YOLACT++ based semantic visual SLAM fo
最近流行将深度学习的方法结合进slam来适应高度动态的场景,但是目前这些基于深度学习的方法都需要预定义移动物体类,比如人,汽车,但是相关语义分割方法提供的客体原始Mask并不完善,不能完全覆盖运动的物体,尤其是物体边界,并且边界信息会泄漏到点云图中,形成大量噪声块,污染了原始的地图。所以需要找到一种方法来修正这些...