docs: add Citation

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fan-ziqi 2024-03-22 00:16:13 +08:00
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[中文文档](README_CN.md) [中文文档](README_CN.md)
Gazebo simulation verification and UnitreeA1 physical deployment for reinforcement learning. "sar" stands for "simulation and real". Simulation verification and physical deployment of the quadruped robot's reinforcement learning algorithm. "sar" stands for "simulation and real".
## Preparation ## Preparation
@ -90,4 +90,17 @@ source devel/setup.bash
rosrun rl_sar rl_real rosrun rl_sar rl_real
``` ```
Press the **R2** button on the remote control to switch the robot to the default standing posture, press **R1** to switch to RL control mode, and press **L2** in any state to switch back to the initial lying posture. The left joystick controls x-axis up and down, controls yaw left and right, and the right joystick controls y-axis left and right. Press the **R2** button on the remote control to switch the robot to the default standing posture, press **R1** to switch to RL control mode, and press **L2** in any state to switch back to the initial lying posture. The left joystick controls x-axis up and down, controls yaw left and right, and the right joystick controls y-axis left and right.
## Citation
Please cite the following if you use this code or parts of it:
```
@software{fan-ziqi2024rl_sar,
author = {fan-ziqi},
title = {{rl_sar: Simulation Verification and Physical Deployment of the Quadruped Robot's Reinforcement Learning Algorithm.}},
url = {https://github.com/fan-ziqi/rl_sar},
year = {2024}
}
```

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[English document](README.md) [English document](README.md)
强化学习的Gazebo仿真验证与UnitreeA1实物部署。"sar"代表"simulation and real" 四足机器人强化学习算法的仿真验证与实物部署。"sar"代表"simulation and real"
## 准备 ## 准备
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``` ```
按下遥控器的**R2**键让机器人切换到默认站起姿态,按下**R1**键切换到RL控制模式任意状态按下**L2**切换到最初的趴下姿态。左摇杆上下控制x左右控制yaw右摇杆左右控制y。 按下遥控器的**R2**键让机器人切换到默认站起姿态,按下**R1**键切换到RL控制模式任意状态按下**L2**切换到最初的趴下姿态。左摇杆上下控制x左右控制yaw右摇杆左右控制y。
## 引用
如果您使用此代码或其部分内容,请引用以下内容:
```
@software{fan-ziqi2024rl_sar,
author = {fan-ziqi},
title = {{rl_sar: Simulation Verification and Physical Deployment of the Quadruped Robot's Reinforcement Learning Algorithm.}},
url = {https://github.com/fan-ziqi/rl_sar},
year = {2024}
}
```