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DeepSLAM: A Robust Monocular SLAM System with Unsupervised Deep Learning

A software system based on deep neural networks which uses camera images to estimate the camera pose and environment map in real time


Visual Simultaneous localisation and mapping otherwise known as SLAM, technique is one of the most important research areas in machine vision and robotics with a broad range of vertical applications spanning from autonomous vehicles to virtual reality. SLAM systems can estimate the robot pose and environment maps and their uses also include robots for inspection, such as visual inspection and assessment of industrial equipment and infrastructures in harsh environments.

The majority of visual SLAM techniques are based on vision geometry and optimisation algorithms and use stereo images. These systems cannot learn automatically from raw images or benefit from continuously increased datasets. There are some visual SLAM techniques which are based on deep neural networks. However, these systems are

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