Open supersupercoconut opened 1 month ago
Hi, @supersupercoconut .
Wheel3DAng
which allows you to leverage planar motion constraint which helps reducing z-axis drift. Hi, @supersupercoconut .
- When you say 6 axis is it mean {gyro, accel}, and 9 axis means {gyro, accel, mag}? If that's the case, MINS uses a 6-axis. If you want to include {mag}, I suggest using {mag} separately as an orientation update method.
- MINS supports multiple assumptions for wheel odometry (see: https://github.com/rpng/MINS/blob/ed6cf522845e09c8ee33da58f27aad46aeba6337/mins/src/update/wheel/WheelTypes.h#L27-L32 ). One common mode is
Wheel3DAng
which allows you to leverage planar motion constraint which helps reducing z-axis drift.
Yes, when I refer to the 6-axis IMU, I'm talking about the gyroscope and accelerometer. I would like to confirm if the data from the /joint_state topic is derived from the fusion of the chassis IMU and a wheel odometer?
In my experience, there are different cases. For example, the KAIST dataset provides direct wheel angular velocity, which you can multiply by wheel radius to get each wheel's velocity. On the other hand, Husky was providing odometry fused with IMU, as you said.
In my experience, there are different cases. For example, the KAIST dataset provides direct wheel angular velocity, which you can multiply by wheel radius to get each wheel's velocity. On the other hand, Husky was providing odometry fused with IMU, as you said.
Thanks for your reply!!!
Thanks for your valuable work! I have some questions regarding this SLAM algorithm: