Web: http://arxiv.org/abs/2205.02940

May 9, 2022, 1:10 a.m. | Pan Ji, Yuan Tian, Qingan Yan, Yuxin Ma, Yi Xu

cs.CV updates on arXiv.org arxiv.org

We present a robust visual-inertial SLAM system that combines the benefits of
Convolutional Neural Networks (CNNs) and planar constraints. Our system
leverages a CNN to predict the depth map and the corresponding uncertainty map
for each image. The CNN depth effectively bootstraps the back-end optimization
of SLAM and meanwhile the CNN uncertainty adaptively weighs the contribution of
each feature point to the back-end optimization. Given the gravity direction
from the inertial sensor, we further present a fast plane detection method …

arxiv cnn constraints slam

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