openai_ros.task_envs.sumit_xl package

Submodules

openai_ros.task_envs.sumit_xl.sumit_xl_room module

class openai_ros.task_envs.sumit_xl.sumit_xl_room.SumitXlRoom

Bases: openai_ros.robot_envs.sumitxl_env.SumitXlEnv

__init__()

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

__module__ = 'openai_ros.task_envs.sumit_xl.sumit_xl_room'

_compute_reward(observations, done)

We give reward to the robot when it gets closer to the desired point. We Dont give it contsnatly, but only if there is an improvement

_get_obs()

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

WALL CLOSE LEFT [1, 1, 9, 0, 0, 0, -1.8, 0.46, 0.01] WALL CLOSE RIGHT [0, 0, 0, 10, 1, 2, -1.8, -0.61, 0.01] WALL BACK [0, 9, 1, 1, 6, 0, -1.8, -0.54, 1.59] WALL FRONT [2, 9, 0, 0, 2, 2, -1.83, 0.51, 1.58]

0 in reality is arround front 0.4, back 0.5, sides 0.3

Returns:

_init_env_variables()

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

_is_done(observations)

_set_action(action)

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

_set_init_pose()

Sets the Robot in its init pose

discretize_scan_observation(data, new_ranges)

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

get_distance_from_desired_point(current_position)

Calculates the distance from the current position to the desired point :param start_point: :return:

get_distance_from_point(pstart, p_end)

Given a Vector3 Object, get distance from current position :param p_end: :return:

get_orientation_euler()

get_vector_magnitude(vector)

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

is_in_desired_position(current_position, epsilon=0.05)

It return True if the current position is similar to the desired poistion

Module contents