Indiana University-Purdue University Indianapolis (IUPUI) / Monocular simultaneous localization and mapping (SLAM) is an important technique that enables very inexpensive environment mapping and pose estimation in
small systems such as smart phones and unmanned aerial vehicles. However, the information generated by monocular SLAM is in an arbitrary and unobservable scale,
leading to drift and making it difficult to use with other sources of odometry for control or navigation. To correct this, the odometry needs to be aligned with metric scale
odometry from another device, or else scale must be recovered from known features in
the environment. Typically known environmental features are not available, and for
systems such as cellphones or unmanned aerial vehicles (UAV), which may experience
sustained, small scale, irregular motion, an IMU is often the only practical option.
Because accelerometers measure acceleration and gravity, an inertial measurement
unit (IMU) must filter out gravity and track orientation with complex algorithms in
order to provide a linear acceleration measurement that can be used to recover SLAM
scale. In this thesis, an alternative method will be proposed, which detects and removes gravity from the accelerometer measurement by using the unscaled direction
of acceleration derived from the SLAM odometry.
Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/14652 |
Date | January 2017 |
Creators | Tucker, Seth C. |
Contributors | El-Sharkawy, Mohamed A. |
Source Sets | Indiana University-Purdue University Indianapolis |
Language | en_US |
Detected Language | English |
Type | Thesis |
Rights | Attribution 3.0 United States, http://creativecommons.org/licenses/by/3.0/us/ |
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