joint_control

3: Joint Control

PID Controller for Joint Servo

1. complete the implementation of PID controller in pid.py
2. use pid_test.ipynb to tuning PID parameters
   • start jupyter notebook in this folder, then you can launch pid_test.ipynb in your web browser
   • follow instruction in notebook, run the code and tune PID parameters
3. save the best parameters in __init__ of class PIDController

Keyframe Motion

1. implement angle interploation method by using splins interpolation or Bezier interpolation in file angle_interpolation.py, please follow instruction in the comments of the file.
   • run simspark and angle_interpolation.py to test hello motion
2. test your implementation with provided keyframes in keyframes folder， for example:
   • import keyframe with from keyframes import hello
   • and set the keyframe in main function, e.g. agent.keyframes = hello()
   • Note: the provided keyframes doesn't have joint RHipYawPitch, please set RHipYawPitch as LHipYawPitch which reflects the real robot.
3. (optional) create your own keyframes

Posture Recognition

use machine learning to recognize robot's posture learn_posture.ipynb, the scikit-learn-intro.ipynb is a good example to follow.

1. preparing dataset (step 1~2 in learn_posture.ipynb )
2. traning dataset, and save the results (step 3~5 in learn_posture.ipynb )
3. getting feature data from simulation and recognize current posture in recognize_posture.py
4. if the result is not good in simulation, adding new train data with add_training_data.ipynb
5. commit file robot_pose.pkl as trained result to git before submission.

Automonous standing up

1. complete the standing_up.py, e.g. call keyframe motion corresponds to current posture
2. Test with the TestStandingUpAgent which turns off all joints regularly to make the robot falls
3. (optional) The TestStandingUpAgent always falls to belly, please also test other suitations: e.g. execute a keyframe motion to make robot falls to another pose and let it stands up.