Contribute to CXavireH/ORB_SLAM3_with_dense_pointcloud development by creating an account on GitHub.
然而,在动态环境中,传统的视觉SLAM算法往往存在显著的映射精度和姿态估计误差。文章提出了一种基于改进的YOLOv8并与ORB-SLAM3融合的方法,旨在解决动态环境中的稠密点云SLAM问题。通过将YOLOv8的实时目标检测和图像分割技术集成到ORB-SLAM3框架中,文章提出的方法在动态环境中实现了高精度和稳健的视觉SLAM。 二、方法 1...
In this paper, we propose a method based on improved YOLOv8 fused with ORB-SLAM3 to address dense point cloud SLAM in dynamic environments. Our proposed method successfully integrates real-time object detection and image segmentation technologies of YOLOv8 into the ORB-SLAM3 framework, achieving ...