Real-time Manhattan World Rotation Estimation in 3D

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We propose three novel algorithms to estimate the full 3D rotation to the surrounding Manhattan World (MW) in as short as 20ms using surface-normals derived from the depth channel of a RGB-D camera. Importantly, this rotation estimate acts as a structure compass which can be used to estimate the bias of an odometry system, such as an inertial measurement unit (IMU), and thus remove its angular drift.


@inproceedings{ straub2015rtmf,
  author = {Straub, Julian and Bhandari, Nishchal and Leonard, John J.  and Fisher III, John W.},
  title = {Real-time Manhattan World Rotation Estimation in 3D},
  year = {2015},
  booktitle = {IROS},
  url =