Digital Signal Processing Reference
In-Depth Information
duty cycle proportionally (e.g., PWM) to the tilt angle by sensing the change in
acceleration due to gravity. Gyros will drift slowly over time and an
accelerometer is needed to correct the gyro's drift. Without an accelerometer to
correct for gyro drift, the tilt error slowly grows to the point where the robot
would lose its balance. Accelerometers will respond more slowly to tilt than the
gyro, so both a gyro and accelerometer is typically needed for each axis that
needs a balance sense.
A complementary filter is used to combine or fuse sensor data from both the
gyro and accelerometer to generate a more accurate tilt angle. Kalman filtering
techniques can be used to improve the accuracy of noisy measurements. Noise
levels are still somewhat high at very low G forces on these low-cost gyros and
accelerometer IC sensors, so currently they are not useful for navigation since
they cannot accurately determine the exact location of a slow moving robot by
integrating the sensor measurements over time.
Analog Devices makes a variety of these sensors and sells small evaluation
boards for them. It is likely that small low-cost sensor modules containing both
a MEMS gyro and an accelerometer with a microcontroller will be available
commercially in the near term.
Figure 13.13
Small sensor board for an aircraft autopilot system. Photograph ©2004 courtesy of
Henrik Christophersen , Georgia Institute of Technology Unmanned Aerial Research Facility.
