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TartanAir: A Dataset to Push the Limits of Visual SLAM
arXiv - CS - Robotics Pub Date : 2020-03-31 , DOI: arxiv-2003.14338
Wenshan Wang; Delong Zhu; Xiangwei Wang; Yaoyu Hu; Yuheng Qiu; Chen Wang; Yafei Hu; Ashish Kapoor; Sebastian Scherer

We present a challenging dataset, the TartanAir, for robot navigation task and more. The data is collected in photo-realistic simulation environments in the presence of various light conditions, weather and moving objects. By collecting data in simulation, we are able to obtain multi-modal sensor data and precise ground truth labels, including the stereo RGB image, depth image, segmentation, optical flow, camera poses, and LiDAR point cloud. We set up a large number of environments with various styles and scenes, covering challenging viewpoints and diverse motion patterns, which are difficult to achieve by using physical data collection platforms.
更新日期:2020-04-01

 

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