update readme

README.md

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-详细使用说明，请参考 https://support.unitree.com/home/zh/developer/rl_example
+# Unitree RL GYM
+
+TODO: 简介
+
+### Installation
+
+1. Create a new python virtual env with python 3.6, 3.7 or 3.8 (3.8 recommended)
+2. Install pytorch 1.10 with cuda-11.3:
+
+   ```
+   pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
+
+   ```
+3. Install Isaac Gym
+
+   - Download and install Isaac Gym Preview 4 from [https://developer.nvidia.com/isaac-gym](https://developer.nvidia.com/isaac-gym)
+   - `cd isaacgym/python && pip install -e .`
+   - Try running an example `cd examples && python 1080_balls_of_solitude.py`
+   - For troubleshooting check docs isaacgym/docs/index.html
+4. Install rsl_rl (PPO implementation)
+
+   - Clone [https://github.com/leggedrobotics/rsl_rl](https://github.com/leggedrobotics/rsl_rl)
+   - `cd rsl_rl && git checkout v1.0.2 && pip install -e .`
+
+### Usage
+
+1. Train:
+   `python legged_gym/scripts/train.py --task=go2`
+
+   * To run on CPU add following arguments: `--sim_device=cpu`, `--rl_device=cpu` (sim on CPU and rl on GPU is possible).
+   * To run headless (no rendering) add `--headless`.
+   * **Important** : To improve performance, once the training starts press `v` to stop the rendering. You can then enable it later to check the progress.
+   * The trained policy is saved in `logs/<experiment_name>/<date_time>_<run_name>/model_<iteration>.pt`. Where `<experiment_name>` and `<run_name>` are defined in the train config.
+   * The following command line arguments override the values set in the config files:
+   * --task TASK: Task name.
+   * --resume: Resume training from a checkpoint
+   * --experiment_name EXPERIMENT_NAME: Name of the experiment to run or load.
+   * --run_name RUN_NAME: Name of the run.
+   * --load_run LOAD_RUN: Name of the run to load when resume=True. If -1: will load the last run.
+   * --checkpoint CHECKPOINT: Saved model checkpoint number. If -1: will load the last checkpoint.
+   * --num_envs NUM_ENVS: Number of environments to create.
+   * --seed SEED: Random seed.
+   * --max_iterations MAX_ITERATIONS: Maximum number of training iterations.
+2. Play:`python legged_gym/scripts/play.py --task=go2`
+    * By default, the loaded policy is the last model of the last run of the experiment folder.
+
+    * Other runs/model iteration can be selected by setting `load_run` and `checkpoint` in the train config.
+
+### Robots Demo
+
+1. Go2
+
+
+
+2. H1
+
+
+
+3. H1-2
+
+https://github.com/user-attachments/assets/a937e9c4-fe91-4240-88ea-d83b0160cad5
+
+4. G1
+