3D Mapping System Estimated from 2D for Low-Cost Devices

Currently, advances in the field of deep learning have made it possible to make improvements in terms of computer vision. This work proposes a system capable of implementing convolutional neural networks that estimate depth together with SLAM techniques to build three-dimensional environments with low-cost devices that can be applied in various tasks that require specific 3D maps.