## Submodules¶

class openai_ros.task_envs.turtlebot3.turtlebot3_world.TurtleBot3WorldEnv[source]
__init__()[source]

This Task Env is designed for having the TurtleBot3 in the turtlebot3 world closed room with columns. It will learn how to move around without crashing.

__module__ = 'openai_ros.task_envs.turtlebot3.turtlebot3_world'
_compute_reward(observations, done)[source]
_get_obs()[source]

Here we define what sensor data defines our robots observations To know which Variables we have acces to, we need to read the TurtleBot2Env API DOCS :return:

_init_env_variables()[source]

Inits variables needed to be initialised each time we reset at the start of an episode. :return:

_is_done(observations)[source]
_set_action(action)[source]

This set action will Set the linear and angular speed of the turtlebot2 based on the action number given. :param action: The action integer that set s what movement to do next.

_set_init_pose()[source]

Sets the Robot in its init pose

discretize_scan_observation(data, new_ranges)[source]

Discards all the laser readings that are not multiple in index of new_ranges value.

get_vector_magnitude(vector)[source]

It calculated the magnitude of the Vector3 given. This is usefull for reading imu accelerations and knowing if there has been a crash :return:

reward_range = None

We set the Observation space for the 6 observations cube_observations = [

round(current_disk_roll_vel, 0), round(y_distance, 1), round(roll, 1), round(pitch, 1), round(y_linear_speed,1), round(yaw, 1),

]