一、mujoco210安装
1.安装MuJoCo
# 下载压缩档
https://mujoco.org/download/mujoco210-linux-x86_64.tar.gz
# 上传到服务器
scp C:\Users\Owner\Downloads\mujoco210-linux-x86_64.tar.gz g7:/home/chenwenze19
# 创建文件夹
mkdir ~/.mujoco
# 解压缩
tar -zxvf mujoco210-linux-x86_64.tar.gz -C ~/.mujoco
添加环境变量
gedit ~/.bashrc
export LD_LIBRARY_PATH=~/.mujoco/mujoco210/bin
source ~/.bashrc
测试mujoco
cd ~/.mujoco/mujoco210/bin
./simulate ../model/humanoid.xml
二、安装mujoco-py
2.1 下载mujoco-py到本地电脑
git clone https://github.com/openai/mujoco-py.git
2.2 创建anaconda环境然后进行安装
这里我创建了一个名为pytorch的python版本为3.8的环境
conda create -n pytorch python=3.8
conda activate pytorch
cd ~/mujoco-py
pip3 install -U 'mujoco-py<2.2,>=2.1'
pip3 install -r requirements.txt
pip3 install -r requirements.dev.txt
python3 setup.py install
2.3 配置.bashrc环境文件
gedit ~/.bashrc
# 在最后添加下面代码然后保存退出文档
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib/nvidia
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/home/zsq/.mujoco/mujoco210/bin:/usr/lib/nvidia
source ~/.bashrc
2.4 测试mujoco-py安装是否成功
python
import mujoco_py
import os
mj_path = mujoco_py.utils.discover_mujoco()
xml_path = os.path.join(mj_path, 'model', 'humanoid.xml')
model = mujoco_py.load_model_from_path(xml_path)
sim = mujoco_py.MjSim(model)
print(sim.data.qpos)
# [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
sim.step()
print(sim.data.qpos)
# [-2.09531783e-19 2.72130735e-05 6.14480786e-22 -3.45474715e-06
# 7.42993721e-06 -1.40711141e-04 -3.04253586e-04 -2.07559344e-04
# 8.50646247e-05 -3.45474715e-06 7.42993721e-06 -1.40711141e-04
# -3.04253586e-04 -2.07559344e-04 -8.50646247e-05 1.11317030e-04
# -7.03465386e-05 -2.22862221e-05 -1.11317030e-04 7.03465386e-05
# -2.22862221e-05]
