Hands-On ROS for Robotics Programming

Environments

An environment is a scenario that models a problem (such as keeping a cart pole standing up) with a minimal interface that an agent can interact with. You can see the cart pole environment in action by running this snippet of code:

$ cd ~/catkin_ws/src/Chapter12_OpenAI_Gym/cart-pole$ conda activate gym(gym) $ python cart-pole_env.py

You should see the cart pole moving and rotating randomly, as shown in the following screenshot:

The content of the script is quite simple:

import gymenv = gym.make('CartPole-v0')env.reset()for _ in range(1000):    env.render()    env.step(env.action_space.sample())env.close()

After importing the gym module, ...