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Found 5 papers, 0 papers with code
FRAME: A Modular Framework for Autonomous Map-merging: Advancements in the Field
In this article, a novel approach for merging 3D point cloud maps in the context of egocentric multi-robot exploration is presented.
RecNet: An Invertible Point Cloud Encoding through Range Image Embeddings for Multi-Robot Map Sharing and Reconstruction
In the field of resource-constrained robots and the need for effective place recognition in multi-robotic systems, this article introduces RecNet, a novel approach that concurrently addresses both challenges.
Irregular Change Detection in Sparse Bi-Temporal Point Clouds using Learned Place Recognition Descriptors and Point-to-Voxel Comparison
Change detection and irregular object extraction in 3D point clouds is a challenging task that is of high importance not only for autonomous navigation but also for updating existing digital twin models of various industrial environments.
Multimodal Dataset from Harsh Sub-Terranean Environment with Aerosol Particles for Frontier Exploration
Thus, there is a need of fusing acquired data from these sensors with data from Radio Detection and Rangings (RADARs) which can penetrate through such particles.
FRAME: Fast and Robust Autonomous 3D point cloud Map-merging for Egocentric multi-robot exploration
This article presents a 3D point cloud map-merging framework for egocentric heterogeneous multi-robot exploration, based on overlap detection and alignment, that is independent of a manual initial guess or prior knowledge of the robots' poses.
