This repository focuses on demonstrating techniques to track kinematics from inertial measurement units (IMUs).
To keep the python modules consistent between users, theimu_envpython environment can be downloaded via conda using the following command:
conda env create -f environment.yml
This installs the python modules from the conda channels and the local modules (i.e.: iotools) from the setup.py file.
The plot shown below was generated using the "executables/data_collection.py" script while an IMU was placed on a rotating stool for 20 seconds.
The end goal will be to generate the cartesian trajectory of the IMU relative to the global earth frame and minimize the sensor drift and noise as much as possible. State estimation algorithms such as the Extended Kalman Filter can be used to reduce the trajectory error.
More to come soon!
- Yost Labs Bluetooth Manual:https://yostlabs.com/wp/wp-content/uploads/pdf/3-Space-Sensor-Users-Manual-Bluetooth-1.pdf