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Published by ibrahimessam on September 10, 2020
TartanAir AirSim Autonomous vehicle data generated to solve Simultaneous Localization and Mapping (SLAM) Simultaneous Localization and Mapping (SLAM) is one of the most fundamental capabilities necessary for robots. Due to the ubiquitous availability of images, Visual SLAM (V-SLAM) has become an important component of many autonomous systems. Impressive progress has been made with both geometric-based methods and learning-based methods. However, developing robust and reliable SLAM methods for real-world applications is still a challenging problem. Real-life environments are full of difficult cases such as light changes or lack of illumination, dynamic objects, and texture-less scenes. This dataset takes advantage of the advancing computer graphics technology and aims to cover diverse scenarios with challenging features in simulation. more info here: https://theairlab.org/tartanair-dataset/