Stereo Visual Inertial Odometry for Robots with Limited Computational Resources*

Current existing stereo visual odometry algorithms are computationally too expensive for robots with restricted resources. Executing these algorithms on such robots leads to a low frame rate and unacceptable decay in accuracy. We modify S-MSCKF, one of the most computationally efficient stereo Visual Inertial Odometry (VIO) algorithm, to improve...

How Do Neural Networks See Depth in Single Images?

Deep neural networks have lead to a breakthrough in depth estimation from single images. Recent work shows that the quality of these estimations is rapidly increasing. It is clear that neural networks can see depth in single images. However, to the best of our knowledge, no work currently exists that analyzes what these networks have learned. In...