Metadata-Version: 2.4
Name: ub-clean-test
Version: 0.11.0
Summary: 机器人控制框架
Author: pengyeqin
Author-email: xxbj433@qq.com
Description-Content-Type: text/markdown
Requires-Dist: numpy>=1.21.0
Requires-Dist: scipy>=1.7.0
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```markdown
# ub-clean-test

[中文版](#chinese) | [English](#english)

---

## <a id="chinese"></a>中文版

一个模块化的机器人控制框架。

### 功能
- **基础控制**：PID、LQR、自适应控制
- **运动学**：逆运动学（速度级、位置级）
- **轨迹规划**：五次多项式平滑运动
- **路径规划**：RRT 快速扩展随机树
- **状态估计**：卡尔曼滤波
- **强化学习**：PPO 近端策略优化
- **自适应控制可视化**：（0.11.0 新增） 动态展示参数调整过程

### 安装
```

pip install ub-clean-test

```

### 快速开始
```python
from ultra_balance import create_robot
robot = create_robot('two_wheel')
robot.start()
```

### 示例
- `demo_trajectory.py`：轨迹规划演示
- `demo_rrt.py`：RRT 路径规划演示
- `demo_ppo.py`：PPO 强化学习演示
- `demo_kalman.py`：卡尔曼滤波演示
- `demo_adaptive.py`：自适应控制演示（0.11.0 新增）

---

<a id="english"></a>English Version

A modular robot control framework.

### Features
- **Control**: PID, LQR, adaptive control
- **Kinematics**: Forward/Inverse kinematics
- **Trajectory Planning**: Quintic polynomial
- **Path Planning**: RRT (Rapidly-exploring Random Tree)
- **State Estimation**: Kalman filter
- **Reinforcement Learning**: PPO (Proximal Policy Optimization)
- **Adaptive Control Visualization**: (new in 0.11.0) Dynamic visualization of gain adaptation

Installation

```
pip install ub-clean-test
```

Quick Start

```python
from ultra_balance import create_robot
robot = create_robot('two_wheel')
robot.start()
```

Modules

· core/: Core algorithms (Kalman filter, PID, etc.)
· planning/: Path planning (A*, RRT)
· learning/: Reinforcement learning (PPO)

### Examples
- `demo_trajectory.py`: Trajectory planning demo
- `demo_rrt.py`: RRT path planning demo
- `demo_ppo.py`: PPO reinforcement learning demo
- `demo_kalman.py`: Kalman filter demo
- `demo_adaptive.py`: Adaptive control demo (new in 0.11.0)
