Get a 2D bipedal walker to walk through rough terrain by applying motor torque.
Reward is given for moving forward, total 300+ points up to the far end. If the robot falls, it gets -100. Applying motor torque costs a small amount of points, more optimal agent will get better score. State consists of hull angle speed, angular velocity, horizontal speed, vertical speed, position of joints and joints angular speed, legs contact with ground, and 10 lidar rangefinder measurements. There's no coordinates in the state vector.
Following are the commands used to train and test the model:
To train the model:
python td3.py trainTo run with pre-trained weights:
python td3.py testThe obtained result:
