CNN-Augmented Visual-Inertial SLAM with Planar Constraints. (arXiv:2205.02940v1 [cs.RO])

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

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