This is a project that uses IMU filter algorithm in ROS(Robot Operating System). The IMU I use is ICM 20602, consisting of a tri-axis gyroscope and a tri-axis accelerometer.
Message containing raw IMU data, including angular velocities and linear accelerations.
imu0(sensor_msgs/Imu)
The fused pose representation.
quaternion(geometry_msg/QuaternionStamped)
ypr(geometry_msgs/Vector3Stamped)
(Mahony_filter) twoKp twoKi
(Madgwick_filter) beta
To tune the dynamic parameters after runnig the node, input
rosrun rqt_configure rqt_reconfigure
According to Madgwick's thesis, the suggested beta = sqrt(3.0f / 4.0f) * gyroMeasError. ICM20602's gyroscope sensitivity erroris ±1%. Thus the default beta is setting to 0.1088. As the specific application, the value can be tuned accoring to response and requriments.
sampleFreq(float, default: 400.0)
You can change its value at the beginning, Such as:
rosrun filter Madgwick_filter _sampleFreq:=200
odom -> imu
So you can open rviz and set the fixed frame "odom", add TF then you can use it to verify the effect directly.
The Madgwick_filter node's effect is acceptable, but the Mahony_filter is disappointing.