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Found 6 papers, 1 papers with code
Benchmarking Classical and Learning-Based Multibeam Point Cloud Registration
However, in the underwater domain, most registration of multibeam echo-sounder (MBES) point cloud data are still performed using classical methods in the iterative closest point (ICP) family.
Neural Network Normal Estimation and Bathymetry Reconstruction from Sidescan Sonar
In this article, we use a neural network to represent the map and optimize it under constraints of altimeter points and estimated surface normal from sidescan.
High-Resolution Bathymetric Reconstruction From Sidescan Sonar With Deep Neural Networks
This is then combined with the indirect but high-resolution seabed slope information from the sidescan to estimate the full bathymetry.
PointNetKL: Deep Inference for GICP Covariance Estimation in Bathymetric SLAM
However, an accurate estimate of the uncertainty of such registration is a key requirement to a consistent fusion of this kind of measurements in a SLAM filter.
Detection and Tracking of General Movable Objects in Large 3D Maps
This paper studies the problem of detection and tracking of general objects with long-term dynamics, observed by a mobile robot moving in a large environment.
Unsupervised Object Discovery and Segmentation of RGBD-images
In this paper we introduce a system for unsupervised object discovery and segmentation of RGBD-images.
