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机器人控制框架

Project description

# 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
- **线性倒立摆 (LIPM)**:双足机器人步态规划基础 (0.12.0 新增)
- **零力矩点 (ZMP)**:双足机器人稳定性判断 (0.13.0 新增)
- **模型预测控制 (MPC)**:步态预测与优化控制 (0.14.0 新增)
- **全身控制 (WBC)**:多任务协调(走路 + 上肢动作)(0.15.0 新增)
- **视觉-语言-动作 (VLA)**:听懂简单指令 (0.16.0 新增)
- **视觉感知 (Vision)**:检测物体颜色和位置 (0.17.0 新增)
- **任务规划 (Task Planning)**:听懂→看懂→行动 (0.18.1 新增)
- **经验记忆 (Experience Memory)**:记住成功经验,下次秒执行 (0.19.0 新增)
- **自动调参 (Auto-Tuning)**:自己找最优控制参数 (0.20.0 新增)
- **状态预测 (State Prediction)**:预判未来轨迹,提前避险 (0.21.0 新增)
- **安全规则库 (Safety Rules)**:定义机器人不能做的事 (0.22.0 新增)
- **自检系统 (Self-Diagnosis)**:检查自身状态,知道能不能干活 (0.23.0 新增)
- **故障恢复 (Fault Recovery)**:检测故障并尝试自动修复 (0.24.0 新增)

### 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)
  • demo_lipm.py:线性倒立摆演示 (0.12.0 新增)
  • demo_zmp.py:ZMP 稳定性演示 (0.13.0 新增)
  • demo_mpc.py:MPC 控制演示 (0.14.0 新增)
  • demo_wbc.py:全身控制演示 (0.15.0 新增)
  • demo_vla.py:VLA 演示 (0.16.0 新增)
  • demo_vision.py:视觉感知演示 (0.17.0 新增)
  • demo_task.py:任务规划演示 (0.18.1 新增)
  • demo_experience.py:经验记忆演示 (0.19.0 新增)
  • demo_autotune.py:自动调参演示 (0.20.0 新增)
  • demo_predict.py:状态预测演示 (0.21.0 新增)
  • demo_safety.py:安全规则演示 (0.22.0 新增)
  • demo_self_diagnosis.py:自检系统演示 (0.23.0 新增)
  • demo_fault_recovery.py:故障恢复演示 (0.24.0 新增)

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
  • Linear Inverted Pendulum Model (LIPM): Foundation for bipedal robot gait planning (new in 0.12.0)
  • Zero Moment Point (ZMP): Bipedal robot stability criterion (new in 0.13.0)
  • Model Predictive Control (MPC): Gait prediction and optimization (new in 0.14.0)
  • Whole Body Control (WBC): Multi-task coordination (walk + arm) (new in 0.15.0)
  • Visual-Language-Action (VLA): Understand simple commands (new in 0.16.0)
  • Vision Perception: Detect object color and position (new in 0.17.0)
  • Task Planning: Understand → See → Act (new in 0.18.1)
  • Experience Memory: Remember successful tasks, execute instantly next time (new in 0.19.0)
  • Auto-Tuning: Find optimal control parameters automatically (new in 0.20.0)
  • State Prediction: Predict future trajectory, avoid danger in advance (new in 0.21.0)
  • Safety Rules: Define what the robot cannot do (new in 0.22.0)
  • Self-Diagnosis: Check own status, know if ready to work (new in 0.23.0)
  • Fault Recovery: Detect faults and try to recover automatically (new in 0.24.0)

Installation

pip install ub-clean-test

Quick Start

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)
  • demo_lipm.py: Linear Inverted Pendulum demo (new in 0.12.0)
  • demo_zmp.py: ZMP stability demo (new in 0.13.0)
  • demo_mpc.py: MPC control demo (new in 0.14.0)
  • demo_wbc.py: Whole Body Control demo (new in 0.15.0)
  • demo_vla.py: VLA demo (new in 0.16.0)
  • demo_vision.py: Vision perception demo (new in 0.17.0)
  • demo_task.py: Task planning demo (new in 0.18.1)
  • demo_experience.py: Experience memory demo (new in 0.19.0)
  • demo_autotune.py: Auto-tuning demo (new in 0.20.0)
  • demo_predict.py: State prediction demo (new in 0.21.0)
  • demo_safety.py: Safety rules demo (new in 0.22.0)
  • demo_self_diagnosis.py: Self-diagnosis demo (new in 0.23.0)
  • demo_fault_recovery.py: Fault recovery demo (new in 0.24.0)

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