Implements the game-inspired curriculum. Args: env_ids (List[int]): ids of environments being reset

Check if environments need to be reset

Computes observations

Compute rewards Calls each reward function which had a non-zero scale (processed in self._prepare_reward_function()) adds eac

Creates simulation, terrain and evironments

Get rotation matrix from the given quaternion. Args: q (np.array[float[4]]): quaternion [w,x,y,z] Returns: np.array[float

check terminations, compute observations and rewards calls self._post_physics_step_callback() for common computations calls

Reset some environments. Calls self._reset_dofs(env_ids), self._reset_root_states(env_ids), and self._resample_commands(env_ids)

Reset selected robots

Does the inverse operation of split_and_pad_trajectories()

Implements a curriculum of increasing commands Args: env_ids (List[int]): ids of environments being reset

Initializes all member classes recursively. Ignores all namse starting with '__' (buit-in methods).

Parses the provided config file, calls create_sim() (which creates, simulation, terrain and environments), initilizes pytorch