Search Results for author:
Found 3 papers, 2 papers with code
A Hybrid Semantic-Geometric Approach for Clutter-Resistant Floorplan Generation from Building Point Clouds
The clutter points are removed whereas the wall, door, and stair points are used for 2D floorplan generation.
LRGNet: Learnable Region Growing for Class-Agnostic Point Cloud Segmentation
3D point cloud segmentation is an important function that helps robots understand the layout of their surrounding environment and perform tasks such as grasping objects, avoiding obstacles, and finding landmarks.
Multi-view Incremental Segmentation of 3D Point Clouds for Mobile Robots
Mobile robots need to create high-definition 3D maps of the environment for applications such as remote surveillance and infrastructure mapping.
Robotics
Cannot find the paper you are looking for? You can
Submit a new open access paper.
