# Mujoco Gym Environment for quadupedal legged locomotion
[](https://pypi.org/project/gym-quadruped/) [](https://github.com/Danfoa/MorphoSymm/actions/workflows/tests.yaml)
# Install Instructions
```bash
pip install gym-quadruped
# or install locally
cd <gym-quadruped root dir>
pip install -e .
```
# Usage Instructions
```python
from gym_quadruped.quadruped_env import QuadrupedEnv
robot_name = "mini_cheetah" # "aliengo", "mini_cheetah", "go2", "hyqreal", ...
scene_name = "flat" # perlin | random_boxes
state_observables_names = tuple(QuadrupedEnv.ALL_OBS) # return all available state observables
env = QuadrupedEnv(robot='mini_cheetah',
scene=scene_name,
base_vel_command_type="human", # "forward", "random", "forward+rotate", "human"
state_obs_names=state_observables_names, # Desired quantities in the 'state'
)
obs = env.reset()
env.render()
for _ in range(10000):
action = env.action_space.sample() * 50 # Sample random action
state, reward, is_terminated, is_truncated, info = env.step(action=action)
if is_terminated:
pass
# Do some stuff
env.render()
env.close()
```
See also `examples` directory.
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