One of our PSSC was to have a functionnal accelerometer for last monday. Despite the fact we didn’t post that day, we did have a working implementation and we were able to compute the inclination angle using the normalized 3D acceleration vector. We did this only with interruptions and without any kind of polling. The code was actually already working at our last demo. But in the meantime we’ve made some improvements that deserve to be described here. We used to detect rising edge of the accelero’s RDY pin to update the values. The rate at which values are calculated depends on the decimation factor chosen. According to the datasheet it spans from 40 Hz to 2560 Hz (with only 4 different values) and because of the fact we need 200 values per second we chose a decimation factor of 32 that enabled us to refresh values at a rate of 400Hz (closest value). Using interruptions at rising edge of RDY pin and then requesting the values from the device using SPI bus protocol was a bit demanding for the processor at this rate. We have therefore chosen not to use the RDY pin to be able to choose more precisely our rate of update. Some changes have also been made on the number of bytes used to represent data and a global coordinate system has been defined for both accelerometer and gyroscope.
Video of our sensorboard displaying the inclination angle using a color led.
Today we also assembled the mechanics of the Zzaag project. We could even try to ride it using the board shipped with. Here is a picture of what it looks like:
We had the time to begin the drivers for our hypothetical encoders (we are not sure to be able to set them on the mechanics) and we will be able to finish them tomorrow to be able to validate another PSSC.
At this point we have several pieces of software that wait to be integrated in our boards softs. The integration of the sensorboard has been started. In the main task an infinite loop wakes up every 5ms (200Hz). We retrieve the values of the accelerometer and the gyroscope that are updated separately in independant tasks. Then we need to give these values to the kalman filter for the final angle to be computed getting rid of the noise. But the kalman filter needs to estimate the next state before correcting the given values. We then need to receive the current values of the commands applied to the motors sent on the CAN bus by the main board. Finally we broadcast the computed angle and angular velocity on the CAN bus.