
#Position Log filename. Use None to disable.
position_log_filename = "math/pos_log.txt"
#position_log_filename = None

#Position Log with Noise filename. Use None to disable.
position_log_noise_filename = "math/pos_log_noise.txt"
#position_log_filename = None

#Command and Update Log filename. Use None to disable.
cmdupd_filename = "math/commands.txt"
#cmdupd_filename = None

#Gaussian noise addition variances
noise_var_x = 3.
noise_var_y = 3.
noise_var_angle = 0.05

#Position Log filename. Use None to disable.
position_log_filename = "math/pos_log.txt"
#position_log_filename = None

#Command and Update Log filename. Use None to disable.
cmdupd_filename = "math/commands.txt"
#cmdupd_filename = None

#Gaussian noise addition variances
noise_var_x = 3.E-5
noise_var_y = 3.E-5
noise_var_angle = 1.

# Process error estimate. The lower (higher negative exponent), more the filter
# becomes like a Low-Pass Filter (higher confidence in the model prediction).
Q = 1e-5

# Measurement error variances (for the R matrix).
# The higher (lower negative exponent), more the filter becomes like a
# Low-Pass Filter (higher possible measurement error).
R_var_x = 3.E-5
R_var_y = 3.E-5
R_var_angle = 3

Add Q (generic) and R (3 values) to get more precise Kalman results
Add Q (generic) and R (3 values) to get more precise Kalman results

  
  #Position Log filename. Use None to disable.
  position_log_filename = "math/pos_log.txt"
- #position_log_filename = None
- 
- #Position Log with Noise filename. Use None to disable.
- position_log_noise_filename = "math/pos_log_noise.txt"
  #position_log_filename = None
  
  #Command and Update Log filename. Use None to disable.
  cmdupd_filename = "math/commands.txt"
  #cmdupd_filename = None
  
  #Gaussian noise addition variances
- noise_var_x = 3.
+ noise_var_x = 3.E-5
- noise_var_y = 3.
+ noise_var_y = 3.E-5
- noise_var_angle = 0.05
+ noise_var_angle = 1.
+ 
+ # Process error estimate. The lower (higher negative exponent), more the filter
+ # becomes like a Low-Pass Filter (higher confidence in the model prediction).
+ Q = 1e-5
+ 
+ # Measurement error variances (for the R matrix).
+ # The higher (lower negative exponent), more the filter becomes like a
+ # Low-Pass Filter (higher possible measurement error).
+ R_var_x = 3.E-5
+ R_var_y = 3.E-5
+ R_var_angle = 3
+ 
Add Q (generic) and R (3 values) to get more precise Kalman results
## Code Before:

#Position Log filename. Use None to disable.
position_log_filename = "math/pos_log.txt"
#position_log_filename = None

#Position Log with Noise filename. Use None to disable.
position_log_noise_filename = "math/pos_log_noise.txt"
#position_log_filename = None

#Command and Update Log filename. Use None to disable.
cmdupd_filename = "math/commands.txt"
#cmdupd_filename = None

#Gaussian noise addition variances
noise_var_x = 3.
noise_var_y = 3.
noise_var_angle = 0.05
## Instruction:
Add Q (generic) and R (3 values) to get more precise Kalman results
## Code After:

#Position Log filename. Use None to disable.
position_log_filename = "math/pos_log.txt"
#position_log_filename = None

#Command and Update Log filename. Use None to disable.
cmdupd_filename = "math/commands.txt"
#cmdupd_filename = None

#Gaussian noise addition variances
noise_var_x = 3.E-5
noise_var_y = 3.E-5
noise_var_angle = 1.

# Process error estimate. The lower (higher negative exponent), more the filter
# becomes like a Low-Pass Filter (higher confidence in the model prediction).
Q = 1e-5

# Measurement error variances (for the R matrix).
# The higher (lower negative exponent), more the filter becomes like a
# Low-Pass Filter (higher possible measurement error).
R_var_x = 3.E-5
R_var_y = 3.E-5
R_var_angle = 3
