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Fall 2019
This thesis proposes a method to estimate robot localization error without having a ground-truth measurement of robot position. Robot localization refers to estimating a robot position and orientation (pose) within a known map, where the error is the difference between the robot’s ground-truth...
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Fall 2019
There has been tremendous research progress in estimating the depth of a scene from a monocular camera image. Existing methods for single-image depth prediction are exclusively based on deep neural networks, and their training can be unsupervised using stereo image pairs, supervised using LiDAR...