try to make a simple two wheel balancing bot (segway bot) without an imu.
Balancing a reverse pendulum and providing heading and absolute World position are two very different problems.
My conclusions from the paper:
1. IMU heading error quickly becomes 10-30 degrees
2. By itself, no IMU can give useful path and heading.
And my conclusions from this mental excursion:
1. Our body also suffers from the same rapid “eyes closed” error accumulation
2. Brooks is correct that environmental references are stronger than symbolic representations (world coordinates), for the robot mobility domain.
3. Vision will be the most powerful sensor my robot already has, among encoders, TOF distance, microphone, and camera
4. Robotics is (still) hard.
Balancing the reverse pendulum is solved by feeding directly the accelerations measured by the IMU to the stabilization control system.
On the other hand for the path and heading problem, those variables you what to measure are second derivatives of the IMU original measured variable (linear and angular accelerations). This means you have to integrate twice the IMU measure in order to get an estimation
of world position and heading.
Integrating sensor signals is tricky and risky, on each subsequent integration step you are not only adding a signal increment, but a bunch of random noise too. This means that depending on the sensor noise and for how long you've estimated the coordinates you'll get an error on those coordinates.
Your conclusions from the paper are correct. In fact, for useful path and heading on mobile robotics statistical filters are used (e.g. the Kalman filter
), mixing different sensor measurements (encoder odometry, GPS, vision estimations,etc..).
Hope i've helped
PS: robotics is still hard yeah, but challenges are fun