This paper presents an efficientdense RGB-D SLAM system, i.e ., CG-SLAM, based on a novel uncertainty-aware 3D Gaussian field with high consistency and geometric stability. Through an in-depth analysis of Gaussian Splatting, we propose several techniques to construct a consistent and stable ...
在现实世界中,环境的动态性,如移动的物体和变化的场景,会阻碍SLAM系统正确估计相机的运动,导致无法有效地构建环境地图。现有的SLAM方法大多基于静态环境的假设,当环境中出现动态障碍物时,这些方法无法提取足够的可靠静态视觉特征,导致特征关联不足,进而影响运动估计的准确性。为了克服这一挑战,文章提出了一种新的密集RG...
This is the official implementation of CG-SLAM: Efficient Dense RGB-D SLAM in a Consistent Uncertainty-aware 3D Gaussian Field. CG-SLAM can achieve state-of-the-art performance in tracking, mapping, rendering, and efficiency.Table of Contents Update Submodule Installation Usage Run ...
In this paper, we propose a dense visual SLAM method for RGB-D cameras that minimizes both the photometric and the depth error over all pixels. In contrast to sparse, feature-based methods, this allows us to better exploit the available information in the image data which leads to higher po...
机译:使用稀疏几何约束改进密集的实时3D Slam 6. Dense RGB-D SLAM with Multiple Cameras [O] . Xinrui Meng, Wei Gao, Zhanyi Hu 2018 机译:带多台摄像机的密集RGB-D SLAM 7. Real-time large-scale dense RGB-D SLAM with volumetric fusion [O] . Whelan, Thomas, Kaess, Michael, Johann...
RoDyn-SLAM: Robust Dynamic Dense RGB-D SLAM with Neural Radiance Fields, Haochen Jiang*, Yueming Xu*, Kejie Li, Jianfeng Feng, Li Zhang IEEE RAL 2024Official implementation of "RoDyn-SLAM: Robust Dynamic Dense RGB-D SLAM with Neural Radiance Fields". Leveraging neural implicit representation ...
Finally, the left static environment is aligned with a state-of-the-art frame-to-model scheme. Experimental results on common RGB-D SLAM benchmark show that the proposed method achieves outstanding performance in dynamic environments. Moreover, it is even comparable to the performance of the ...
we show for the first time that representing a scene by a 3D Gaussian Splatting radiance field can enable dense SLAM using a single unposed monocular RGB-D camera. Our method, SplaTAM, addresses the limitations of prior radiance field-based representations, including fast rendering and optimizatio...
ManhattanSLAM is a real-time SLAM library forRGB-Dcameras that computes the camera pose trajectory, a sparse 3D reconstruction (containing point, line and plane features) and a dense surfel-based 3D reconstruction. Further details can be found in the related publication. The code is based onORB...
rosrun ORB_SLAM2 RGBD PATH_TO_VOCABULARY PATH_TO_SETTINGS_FILE 8. Processing your own sequences You will need to create a settings file with the calibration of your camera. See the settings file provided for the TUM and KITTI datasets for monocular, stereo and RGB-D cameras. We use the...