Calibration Function
NadaSaad-D8 opened this issue · 6 comments
hello Kiris, thank you so much for your great work i am new to MPU and it is really helpful , i have a question i cannot understand the algorithm of the calibration function , could you send me any paper that talks about calibration you followed in your code ?
thanks for your reply ,
so i have many questions if you have time i will be thankfull if you explained this , i searched alot and the calibration functions are different from yours whatever i don't fully understand them , i got that the idea that i calculate many samples and got the average then subtract it from from subsequent data. but when i follow the code i didn't find it that way
FIRST : what are you reading here ? , why don't we say i read for example 1000 sample so i will divide by 1000 after reading them
readBytes(MPU6050_ADDRESS, FIFO_COUNTH, 2, &data[0]); // read FIFO sample count
fifo_count = ((uint16_t)data[0] << 8) | data[1];
packet_count = fifo_count/12;// How many sets of full gyro and accelerometer data for averaging
SECOND :
Next step is simple we are reading the data (Packet count number) then divided them by packet count to get average
till we reach this , i didn't get what is the meaning of removing sensor senstivity, how is this related to gravity
and then dividing by 4 , and in gyro dividing by 8
if(accel_bias[2] > 0L) {accel_bias[2] -= (int32_t) accelsensitivity;} // Remove gravity from the z-axis accelerometer bias calculation
else {accel_bias[2] += (int32_t) accelsensitivity;}
// Construct the gyro biases for push to the hardware gyro bias registers, which are reset to zero upon device startup
data[0] = (-gyro_bias[0]/4 >> 8) & 0xFF; // Divide by 4 to get 32.9 LSB per deg/s to conform to expected bias input format
data[1] = (-gyro_bias[0]/4) & 0xFF; // Biases are additive, so change sign on calculated average gyro biases
data[2] = (-gyro_bias[1]/4 >> 8) & 0xFF;
data[3] = (-gyro_bias[1]/4) & 0xFF;
data[4] = (-gyro_bias[2]/4 >> 8) & 0xFF;
data[5] = (-gyro_bias[2]/4) & 0xFF;
i am so sorry if the questions are trivial , thanks in advance
Hi Kris, your simple method for calibration is very effective, however I wanted to implement an even more accurate calibration method that are suited for commercial applications of autonomous vehicles. Are there any you would recommend?
Thanks in advance!