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20172020
most citedMultiple Object Detection, Tracking and Long-Term Dynamics Learning in Large 3D Maps

8 citations · 18 across the 3 of their papers we have counts for

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5 papers · 1 filter

cs.RO2020

Towards Autonomous Industrial-Scale Bathymetric Surveying

Ignacio Torrobam Nils Bore, John Folkesson

Both higher efficiency and cost reduction can be gained from automating bathymetric surveying for offshore applications such as pipeline, telecommunication or power cables installa…

cs.RO2020

PointNetKL: Deep Inference for GICP Covariance Estimation in Bathymetric SLAM

Ignacio Torroba, Christopher Iliffe Sprague, Nils Bore +1

Registration methods for point clouds have become a key component of many SLAM systems on autonomous vehicles. However, an accurate estimate of the uncertainty of such registration…

cs.RO20183 cited

Detection and Tracking of General Movable Objects in Large 3D Maps

Nils Bore, Johan Ekekrantz, Patric Jensfelt +1

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. A key problem is that…

cs.RO20188 cited

Multiple Object Detection, Tracking and Long-Term Dynamics Learning in Large 3D Maps

Nils Bore, Patric Jensfelt, John Folkesson

In this work, we present a method for tracking and learning the dynamics of all objects in a large scale robot environment. A mobile robot patrols the environment and visits the di…

cs.RO20177 cited

Unsupervised Object Discovery and Segmentation of RGBD-images

Johan Ekekrantz, Nils Bore, Rares Ambrus +2

In this paper we introduce a system for unsupervised object discovery and segmentation of RGBD-images. The system models the sensor noise directly from data, allowing accurate segm…