173 lines
6.5 KiB
Markdown
Executable File
173 lines
6.5 KiB
Markdown
Executable File
# Sim-to-Real project on Unitree Go2
|
|
|
|
## Overview
|
|
|
|
This repository is forked from [walk-these-ways](https://github.com/Improbable-AI/walk-these-ways), which is a Go1 Sim-to-Real Locomotion Starter Kit. It seems that [walk-these-ways](https://github.com/Improbable-AI/walk-these-ways) can be untilized on Unitree [A1](https://github.com/fan-ziqi/dog_rl_deploy) with simple modifications, since those robots are base on [unitree-legged-sdk](https://github.com/unitreerobotics/unitree_legged_sdk).
|
|
|
|
However, the brand-new architecture [unitree-sdk2 ](https://github.com/unitreerobotics/unitree_sdk2)is not base on UDP anymore, so this project aims to train and deploy walk-these-ways on Unitree Go2 by modifying SDK interfaces.
|
|
|
|
## Requirements
|
|
* pytorch 1.10 with cuda-11.3
|
|
* Isaac Gym
|
|
* Nvidia GPU with at least 8GB of VRAM
|
|
|
|
---
|
|
## Train
|
|
Clone this repository and install:
|
|
|
|
``` bash
|
|
git clone https://github.com/Teddy-Liao/walk-these-ways-go2.git
|
|
cd walk-these-ways-go2
|
|
pip install -e .
|
|
```
|
|
|
|
Start training:
|
|
```bash
|
|
python scripts/train.py
|
|
```
|
|
|
|
`go2_gym` and `go2_gym_learn` folders are the main folders for training process.
|
|
|
|
Play the model:
|
|
```bash
|
|
cd scripts
|
|
python play.py
|
|
```
|
|
|
|
|
|
Go2 pretrained model is provided in [./runs](runs/gait-conditioned-agility/pretrain-go2), you can choose whether to use provide pretrained model by modifying the label line `label = "gait-conditioned-agility/pretrain-go2/train"` to your own trained model.
|
|
|
|
### Known Issues
|
|
* `flip_visual_attachments` in [go2_config](go2_gym/envs/go2/go2_config.py) should be set to `True`, otherwise errors would occur when visualizing.
|
|
* To change configuration parameters of env or the robot, you should modify parameters in [go2_config](go2_gym/envs/go2/go2_config.py), not in [legged_robot_config](go2_gym/envs/base/legged_robot_config.py)
|
|
|
|
|
|
---
|
|
## Deploy on PC
|
|
Trained policy is only supported to be deployed through your PC or laptop now, because I am not familiar with Jetson Orin, and hope I can fix it and deploy on Jetson Orin.
|
|
|
|
### Requirements
|
|
#### Install LCM
|
|
Since [walk-these-ways](https://github.com/Improbable-AI/walk-these-ways) implement an interface based on Lightweight Communications and Marshalling ([LCM](https://github.com/lcm-proj/lcm)) to pass sensor data, motor commands, and joystick state between their code and the low-level control SDK provided by Unitree, LCM should be installed firstly in your PC or laptlop.
|
|
|
|
Clone LCM repository to any location (where you usually place installed softwares), then install LCM:
|
|
```bash
|
|
git clone https://github.com/lcm-proj/lcm.git
|
|
mkdir build
|
|
cd build
|
|
cmake ..
|
|
make
|
|
sudo make install
|
|
```
|
|
|
|
#### Unitree_SDK2
|
|
unitree_sdk2 has been inclued in `go2_gym_deploy/unitree_sdk2_bin/library/unitree_sdk2`, you can also clone from [Unitree Robotics](https://github.com/unitreerobotics/unitree_sdk2) to make sure the sdk is updated version.
|
|
|
|
```bash
|
|
cd go2_gym_deploy/unitree_sdk2_bin/library/unitree_sdk2
|
|
```
|
|
Delete build file
|
|
```bash
|
|
rm -r build
|
|
```
|
|
Install and build:
|
|
```bash
|
|
sudo ./install.sh
|
|
mkdir build
|
|
cd build
|
|
cmake ..
|
|
make
|
|
```
|
|
|
|
### Build lcm_position_go2
|
|
`go2_gym_deploy/unitree_sdk2_bin/lcm_position_go2.cpp` is the core file of this project, which is similar to `lcm_position.cpp` in [walk-these-ways](https://github.com/Improbable-AI/walk-these-ways), but replace unitree_legged_sdk with unitree_sdk2.
|
|
|
|
Build lcm_position_go2 and generate runfile `lcm_position_go2`
|
|
```bash
|
|
cd go2_gym_deploy
|
|
rm -r build
|
|
mkdir build
|
|
cd build
|
|
cmake ..
|
|
make -j
|
|
```
|
|
|
|
All LCM messages files in `go2_gym_deploy/lcm_types` are set as the same format shown in [walk-these-ways](https://github.com/Improbable-AI/walk-these-ways) to ensure successful connection with python files. LCM message files are provided in this project, and you can also generate customized LCM message files through the following instructions:
|
|
|
|
`xxx_lcmt.hpp` files are generated by:
|
|
```bash
|
|
lcm-gen -x xxx.lcm
|
|
```
|
|
|
|
### Verify connection
|
|
Connect your PC/Laptop with Go2 robot with ethernet cable and check connection by:
|
|
```bash
|
|
ping 192.168.123.161
|
|
```
|
|
|
|
Check the network interface address, and copy the network interface address.
|
|
```bash
|
|
ifconfig
|
|
```
|
|
If error occurs, please check [Unitree Support](https://support.unitree.com/home/zh/developer/Quick_start) for details.
|
|
|
|
### Test communication between LCM and unitree_sdk2
|
|
```bash
|
|
cd go2_gym_deploy/build
|
|
sudo ./lcm_position_go2 enx10086
|
|
```
|
|
Aeplace `enx10086` with your own network interface address. According to the messages shown in terminal, press `Enter` for several times and the communication between LCM and unitree_sdk2 will set up.
|
|
|
|
This command will automatically shut down Unitree sport_mode Service and set the robot to LOW-LEVEL. Please make sure This will Go2 is hung up or lie on the ground.
|
|
|
|
You can verify LCM send by opening a new terminal:
|
|
```bash
|
|
cd go2_gym_deploy/build
|
|
sudo ./lcm_receive
|
|
```
|
|
|
|
### Load and run policy
|
|
Open a new terminate and run:
|
|
```bash
|
|
cd go2_gym_deploy/scripts
|
|
python deploy_policy.py
|
|
```
|
|
According to the hints shown in terminal, Press button [R2] to start the controller. You can check RC mapping in the following subsection.
|
|
|
|
|
|
### Joystick Mapping
|
|
|
|
|
|
|
|
|
|
To view the details of joystick mapping or even modify default mapping logic, please refer to the `get_command` function within the [cheetah_state_estimator.py](go2_gym_deploy/utils/cheetah_state_estimator.py) file. In this project, the default gait is set to trot.
|
|
|
|
|
|
**Caution**:
|
|
* Press [L2+B] to switch to damping mode if any unexpected situation occurs!!!
|
|
* This is research code; use at your own risk; we do not take responsibility for any damage.
|
|
|
|
Test Video on Unitree Go2:
|
|
- Test in my bedroom: https://www.bilibili.com/video/BV1tQ4y1c7ZG/?spm_id_from=333.999.0.0&vd_source=07873ebe2a113dac57775e264a210929
|
|
- Test by other contributors: https://www.bilibili.com/video/BV1Ut421H7Fr/?spm_id_from=333.1007.top_right_bar_window_history.content.click&vd_source=07873ebe2a113dac57775e264a210929
|
|
|
|
|
|
---
|
|
## Deploy on Nvidia Jetson Orin
|
|
|
|
To be continue:
|
|
|
|
|
|
---
|
|
|
|
🌟🌟🌟 **Please star this repository if it does help you! Many Thanks!**
|
|
|
|
## Acknowledgements
|
|
* Many thanks to [Leolar](https://github.com/NihaoyaLeolar), who provide Nvidia 3060ti and supporting.
|
|
* Many thanks to [Jony](https://github.com/jonyzhang2023) and Peter for their support and encourage me to learn basic kownledge about RL.
|
|
* Many thanks to [Simonforyou](https://github.com/Simonforyou), who provide Go2 pretrained model.
|
|
|
|
## TO DO
|
|
- [x] Do not inherit config and env from go1_gym, build customized config and env files for Go2
|
|
- [ ] Deploy on Jeston Orin Nano
|