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feat: add Learning-Based Accel/Brake Map Calibrator #231

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Description

This is the PR regarding the learning-based vehicle calibration for longitudinal dynamics already discussed and presented in the discussion thread and in the Planning and Control meeting.

Tests performed

This calibrator has been tested in simulation and real vehicles. We've been using the calibrator for a different range of vehicles in Pix Moving with high accuracy.

Additional materials here:
Pix_Longitudinal_Calibration.pdf
Calibration.pptx

Effects on system behavior

This new calibrator improves the previous one in different aspects:

  1. real data are interpolated with a neural network, which is able to provide a very accurate and smooth map, and can capture the non-linearities of the system;

  2. the whole calibration process is very user-friendly, fast and efficient;

  3. you don't need a huge amount of data for training the neural network, making the data collection process faster;

  4. the learning-based approach can be easily adapted to different kind of scenarios, and not solely on the longitudinal dynamic. In my previous pull request for example, I also included the calibration for steering/parking scenarios, just by adding 1 input to the network;

  5. It can be used with a diverse range of vehicles, with different dynamics, kinematics, engines and transmission systems;

  6. It has been tested in simulation and with real vehicles. We now use it for calibrating our vehicles in Pix Moving.

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github-actions bot commented Mar 28, 2025

Thank you for contributing to the Autoware project!

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@CristianGariboldi
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@xmfcx Hi, just for your information, I opened the previous pull request in Autoware Tools, as you suggested.

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xmfcx commented Apr 15, 2025

@takayuki5168 -san, could you review the autoware_debug_tools/frequent_log_checker.py changes?

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xmfcx commented Apr 18, 2025

Spell check issue should be fixed once we merge:

CristianGariboldi and others added 9 commits April 19, 2025 09:45
Signed-off-by: CristianGariboldi <gariboldicristian@gmail.com>
Signed-off-by: CristianGariboldi <gariboldicristian@gmail.com>
Signed-off-by: CristianGariboldi <gariboldicristian@gmail.com>
Signed-off-by: CristianGariboldi <gariboldicristian@gmail.com>
Signed-off-by: CristianGariboldi <gariboldicristian@gmail.com>
Signed-off-by: CristianGariboldi <gariboldicristian@gmail.com>
Signed-off-by: CristianGariboldi <gariboldicristian@gmail.com>
Signed-off-by: Cristian Gariboldi <gariboldicristian@gmail.com>
Signed-off-by: CristianGariboldi <gariboldicristian@gmail.com>
@xmfcx xmfcx force-pushed the learning_based_calibrator branch from 8d03cb8 to 72e4bbb Compare April 19, 2025 06:45
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xmfcx commented Apr 21, 2025

I'll test it with AWSIM Labs and report my findings.

AWSIM Labs was calibrated with https://github.com/autowarefoundation/autoware_universe/tree/main/vehicle/autoware_accel_brake_map_calibrator before.

The calibration results are in https://github.com/autowarefoundation/autoware_launch/blob/main/vehicle/awsim_labs_vehicle_launch/awsim_labs_vehicle_launch/config/raw_vehicle_cmd_converter/raw_vehicle_cmd_converter.param.yaml and it is used while driving.

I will also calibrate with your tool to see how it differs.

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3 participants