ethz-asl / data-driven-dynamics

Data Driven Dynamics Modeling for Aerial Vehicles
Other
98 stars 14 forks source link

Simulation and testing problem (inconsistent behavior) #198

Closed a3g34n closed 2 years ago

a3g34n commented 2 years ago

Hello,

I am having a problem with simulating the model on Gazebo. When I try to take off the drone take-offs successfully but soon it starts to oscillate then gets out of control and crashes. I tried both my own log files and the example default log file supplied from the data-driven-dynamics repo. I am sending command take-off from qgroundcontrol. Thank you)))

manumerous commented 2 years ago

Thank you for reporting this issue. :) We are happy to help you and to further improve the pipeline. For this we might need some more information. Could you share the full results file you obtain when using the default log? it should be located in the model_results folder.

a3g34n commented 2 years ago

quadrotor_model.zip I build the data-driven-dynamics to PX4-Autopilot/build/px4_sitl_default/data-driven-dynamics

a3g34n commented 2 years ago

Should I open any different log file setting from pixhawk parameters on my quad? Or standart log files are enough?

Jaeyoung-Lim commented 2 years ago

@AEGEAN99 Could you also share the full log displayed on your terminal?

a3g34n commented 2 years ago

of course here my termina when training: `make estimate-model model=quadrotor_model log=resources/quadrotor_model.ulg python3 Tools/parametric_model/generate_parametric_model.py \ --config /home/a3g34n/PX4-Autopilot/build/px4_sitl_default/data-driven-dynamics-master/Tools/parametric_model/configs/quadrotor_model.yaml \ --data_selection False \ --plot True \ resources/quadrotor_model.ulg Visual Data selection enabled: False

                                Data Processing                                  
  ===============================================================================
  Initializing of configuration successful. 
  Resample frequency:  250.0 Hz
  Loading uLog file:  resources/quadrotor_model.ulg
  Loading topics:
  actuator_outputs
  vehicle_local_position
  vehicle_attitude
  vehicle_angular_velocity
  sensor_combined
  Starting data resampling of topic types:  dict_keys(['actuator_outputs', 'vehicle_local_position', 'vehicle_attitude', 'vehicle_angular_velocity', 'sensor_combined'])
  Resampling |################################| 6/5
  Resampling |################################| 7/5Initializing of configuration successful. 
  -------------------------------------------------------------------------------
  Initialized dataframe with the following columns: 
  ['timestamp', 'u0', 'u1', 'u2', 'u3', 'vx', 'vy', 'vz', 'q0', 'q1', 'q2', 'q3', 'ang_vel_x', 'ang_vel_y', 'ang_vel_z', 'ang_acc_b_x', 'ang_acc_b_y', 'ang_acc_b_z', 'acc_b_x', 'acc_b_y', 'acc_b_z']
  Data contains  14775 timestamps.
  Computing force features for rotor: front right rotor
  Computing moment features for rotor: front right rotor
  Computing force features for rotor: back left rotor
  Computing moment features for rotor: back left rotor
  Computing force features for rotor: front left rotor
  Computing moment features for rotor: front left rotor
  Computing force features for rotor: back right rotor
  Computing moment features for rotor: back right rotor
  Cramer-Rao Bounds for force parameters:
  vertical_rot_drag_lin      0.012782946245478023
  vertical_rot_thrust_lin    0.02641080802919156
  vertical_rot_thrust_quad   0.011493031809214254
  c_d_fuselage_x     0.013983358667215987
  c_d_fuselage_y     0.01915150130118305
  c_d_fuselage_z     0.09617539023560966
  Cramer-Rao Bounds for moment parameters:
  vertical_c_m_leaver_quad   0.6704594437261402
  vertical_c_m_leaver_lin    0.43084225232492834
  vertical_c_m_drag_z_quad   0.12862700319155235
  vertical_c_m_drag_z_lin    0.911563984500324
  vertical_c_m_rolling   1.1950003635205881
  ===============================================================================
                          Preparing Model Features                               
  ===============================================================================
  ===============================================================================
                              Initialize Optimizer                               
                                  QPOptimizer
  ===============================================================================
  Define and solve problem:
  min_c (X * c -y)^T * (X * c -y)
   s.t. G * c <= h
  Initialized with the following coefficients: 
  ['vertical_rot_drag_lin', 'vertical_rot_thrust_lin', 'vertical_rot_thrust_quad', 'vertical_c_m_leaver_quad', 'vertical_c_m_leaver_lin', 'vertical_c_m_drag_z_quad', 'vertical_c_m_drag_z_lin', 'vertical_c_m_rolling', 'c_d_fuselage_x', 'c_d_fuselage_y', 'c_d_fuselage_z']
  Fixed Coefficients: Value
  -------------------------------------------------------------------------------
  Bounded Coefficients: (Min Value, Max Value)
  vertical_rot_drag_lin:  (0.0, 2.0)
  vertical_rot_thrust_lin:  (-5.0, 0.0)
  vertical_rot_thrust_quad:  (0.0, 50.0)
  vertical_c_m_leaver_quad:  (0.0, 2.0)
  vertical_c_m_leaver_lin:  (-1.0, 0.0)
  vertical_c_m_drag_z_quad:  (0.0, 2.0)
  vertical_c_m_drag_z_lin:  (-1.0, 0.0)
  vertical_c_m_rolling:  (0.0, 2.0)
  c_d_fuselage_x:  (0.0, 2.0)
  c_d_fuselage_y:  (0.0, 2.0)
  c_d_fuselage_z:  (0.0, 2.0)
  [ 1.59066672e-01 -1.38275472e-01  4.19292061e+00  3.39425013e-01
    1.88560297e-20  5.07582893e-01 -3.12479704e-02  7.30058131e-22
    2.08259718e-03  1.08326852e-02 -6.22803436e-13]
  ===============================================================================
                             Optimization Results                                
  ===============================================================================
                             Optimal Coefficients                              
  -------------------------------------------------------------------------------
  c_d_fuselage_x: 0.002082597182204064
  c_d_fuselage_y: 0.010832685190091253
  c_d_fuselage_z: -6.228034359331524e-13
  vertical_c_m_drag_z_lin: -0.03124797041333541
  vertical_c_m_drag_z_quad: 0.5075828926443368
  vertical_c_m_leaver_lin: 1.885602973253947e-20
  vertical_c_m_leaver_quad: 0.33942501322805907
  vertical_c_m_rolling: 7.300581311503944e-22
  vertical_rot_drag_lin: 0.15906667162903768
  vertical_rot_thrust_lin: -0.13827547174291024
  vertical_rot_thrust_quad: 4.19292060688978

  -------------------------------------------------------------------------------
                              Optimization Metrics                               
  -------------------------------------------------------------------------------
  R2: 0.9876949185774294
  RMSE: 0.609447037495574

  -------------------------------------------------------------------------------
  Complete results saved to: 
  model_results/multirotor_model_2022-04-22-16-07-16.yaml

`

a3g34n commented 2 years ago

and figures Figure_1 Figure_2 Figure_3 Figure_5 :

Jaeyoung-Lim commented 2 years ago

@AEGEAN99 Could you try with the "LinearRegressor" Instead of the "QPOptimiser"?

https://github.com/ethz-asl/data-driven-dynamics/blob/a4162f876bd01f5507cee190521206c913c9ae10/Tools/parametric_model/configs/quadrotor_model.yaml#L74

also might help if you updte to latest master

a3g34n commented 2 years ago

Actually I dont know how to change optimizer. Should I download the latest master PX4-Autopilot? Or should I install the version in your repo?

Jaeyoung-Lim commented 2 years ago

@AEGEAN99 Sorry I modified my initial response.

No, the latest master of this repo

a3g34n commented 2 years ago

okay I am trying now

Jaeyoung-Lim commented 2 years ago

@AEGEAN99 The plots remind me of a problem that I fixed a while ago: https://github.com/ethz-asl/data-driven-dynamics/pull/193 Probably worth checking if the version you are using has the changes included

a3g34n commented 2 years ago

still not working, Here is latest one with qpoptimizer Figure_1 Figure_2 Figure_3 Figure_5 Residual_Visualization

a3g34n commented 2 years ago

And here latest with linearRegressor Figure_1 Figure_2 Figure_3 Figure_5 Residual_Visualization

a3g34n commented 2 years ago

This happens much more slower

https://user-images.githubusercontent.com/62438751/164732107-130c77c6-11ac-4598-8abe-d5402b182809.mp4

Jaeyoung-Lim commented 2 years ago

@AEGEAN99 Ah, now it is working.

Could you try

make estimate-model model=quadrotor_model log=resources/quadrotor_model_trajectory.csv
a3g34n commented 2 years ago

with linearRegressor?

Jaeyoung-Lim commented 2 years ago

@AEGEAN99 Yes, it is basically just swapping the log

a3g34n commented 2 years ago

It is working but has small oscillations like vibration

https://user-images.githubusercontent.com/62438751/164733933-a0de9032-6568-45f8-b60c-f0d51dc600f4.mp4

n

a3g34n commented 2 years ago

Here is the figures of the model. Are they satisfying? And have you determined the problem? Thank you:DD Figure_1 Figure_2 Figure_3 Figure_5 Residual_Visualization

Jaeyoung-Lim commented 2 years ago

@AEGEAN99 Yes, so this means that it has successfully estimated the dynamics.

I am not sure why the vehicle is oscillating, but probably coming from the fact that the moment parameter estimation is not perfect.

a3g34n commented 2 years ago

But when I try the quadrotor_model.csv it agin crashes

a3g34n commented 2 years ago

What should I do for my own log files

Jaeyoung-Lim commented 2 years ago

@AEGEAN99 Yes, because it does not contain enough information - as you can see in the logs there is no angular excitation of the system and the system is unable to successfully estimate the correct parameters

Same for your own logs - You need a log that has enough information to estimate the parameters.

@manumerous Probably we should remove the degenerate logs?

manumerous commented 2 years ago

Thanks for taking over Jay!

Yes I agree with you. I will quickly make a PR and put the trajectory log as our default log. That is indeed confusing.

Furthermore I think this issue points towards the fact that we need to improve the user feedback on the estimated parameters.

@AEGEAN99 as Jay already pointed out estimating the angular dynamics is usually harder than the linear ones. Can you try to fly some maneuvers where you have a lot of angular acceleration and try the pipeline again?

manumerous commented 2 years ago

Adressed in #199

a3g34n commented 2 years ago

Thank you so much!! I will try flying the drone next weeks and update this comment. I hope that works. Thank you for your all effort))))))

manumerous commented 2 years ago

Thanks for reporting! Feel free to close the issue if your problem is solved.