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.. | ||
env_randomizers | ||
__init__.py | ||
bullet_client.py | ||
env_randomizer_base.py | ||
minitaur_alternating_legs_env_example.py | ||
minitaur_alternating_legs_env.py | ||
minitaur_ball_gym_env_example.py | ||
minitaur_ball_gym_env.py | ||
minitaur_derpy.py | ||
minitaur_four_leg_stand_env_example.py | ||
minitaur_four_leg_stand_env.py | ||
minitaur_gym_env_example.py | ||
minitaur_gym_env.py | ||
minitaur_logging_pb2.py | ||
minitaur_logging.proto | ||
minitaur_logging.py | ||
minitaur_proto_dump_example.py | ||
minitaur_raibert_controller_example.py | ||
minitaur_raibert_controller.py | ||
minitaur_rainbow_dash.py | ||
minitaur_randomize_terrain_gym_env_example.py | ||
minitaur_randomize_terrain_gym_env.py | ||
minitaur_reactive_env_example.py | ||
minitaur_reactive_env.py | ||
minitaur_stand_gym_env_example.py | ||
minitaur_stand_gym_env.py | ||
minitaur_trotting_env_example.py | ||
minitaur_trotting_env.py | ||
minitaur.py | ||
motor.py | ||
README.md | ||
simple_ppo_agent_example.py | ||
simple_ppo_agent.py | ||
timestamp_pb2.py | ||
timestamp.proto | ||
vector_pb2.py | ||
vector.proto |
Simulated Minitaur Environments
This folder contains a number of simulated Minitaur environments implemented using pybullet.
The following two environments are used in the RSS paper "Sim-to-Real: Learning Agile Locomotion For Quadruped Robots":
- Galloping environment: minitaur_reactive_env.py
- Trotting environment: minitaur_trotting_env.py
The rest are experimental environments.
Prerequisites
Install TensorFlow
Install OpenAI gym
pip install gym
Install ruamel.yaml
pip install ruamel.yaml
Examples
To run a pre-trained PPO agent that performs the galloping gait
python minitaur_reactive_env_example.py
To run a pre-trained PPO agent that performs trotting gait
python minitaur_trotting_env_example.py
Authors
- Jie Tan
- Tingnan Zhang
- Erwin Coumans
- Atil Iscen
- Yunfei Bai
- Danijar Hafner
- Steven Bohez
- Vincent Vanhoucke