198 lines
4.7 KiB
Markdown
198 lines
4.7 KiB
Markdown
# Origincar Simulation
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基于 MotrixSim 的阿克曼小车仿真，支持键盘控制和 HTTP API 局域网共享。
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## 依赖
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| 依赖 | 说明 | 安装 |
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|------|------|------|
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| Python ≥3.13 | 运行环境 | `brew install python` 或 [python.org](https://python.org) |
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| [uv](https://docs.astral.sh/uv/) | 包管理器 | `curl -LsSf https://astral.sh/uv/install.sh \| sh` |
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| `motrixsim-core` | 物理仿真引擎 | `uv sync` 自动安装 |
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| `pillow` | 摄像头图像转 JPEG | `uv sync` 自动安装 |
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```bash
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# 克隆后一键安装
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uv sync
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```
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> `mxpython` 是 motrixsim-core 自带的启动器，**macOS 上必须使用**（主线程需保留给渲染），Linux / Windows 可直接用 `python`。
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## 启动
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```bash
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# macOS
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uv run mxpython main.py
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# Linux / Windows
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uv run python main.py
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```
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## HTTP API（端口 8765）
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仿真启动后，局域网内其他设备可通过 HTTP 获取摄像头图像、IMU 数据和发送控制指令。
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### GET `/image`
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获取前置摄像头最新 JPEG 图像。浏览器可直接打开。
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```bash
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# 浏览器
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http://<仿真机IP>:8765/image
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# curl
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curl http://1{IP}:8765/image -o frame.jpg
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# Python
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import requests
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r = requests.get("http://{IP}:8765/image")
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with open("frame.jpg", "wb") as f:
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f.write(r.content)
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```
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### GET `/state`
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获取小车当前状态（JSON）。
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```bash
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curl http://{IP}:8765/state
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```
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返回示例：
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```json
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{
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"x": -2.0,
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"y": -2.3,
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"z": 0.08,
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"yaw_deg": 0.0,
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"speed_target": 1.0,
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"speed_actual": 0.98,
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"steer_target": 0.0,
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"speed_amp": 1.0,
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"steer_amp": 0.35
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}
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```
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### GET `/imu`
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获取 IMU 数据（含 MPU6050 噪声），JSON。
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```bash
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curl http://{IP}:8765/imu
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```
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返回示例：
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```json
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{
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"orientation": {"w": 1.0, "x": 0.0, "y": 0.0, "z": 0.0},
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"angular_velocity": {"x": 0.001, "y": -0.003, "z": 0.008},
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"linear_acceleration": {"x": 0.02, "y": -0.01, "z": 9.81}
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}
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```
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噪声参数（MPU6050 级别）：
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- 陀螺仪白噪声 σ = 0.01 rad/s，bias 随机游走
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- 加速度计白噪声 σ = 0.05 m/s²，bias 随机游走
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### POST `/cmd`
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发送控制指令（JSON）。
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```bash
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curl -X POST http://{IP}:8765/cmd \
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-H "Content-Type: application/json" \
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-d '{"speed": 1.0, "steer": 0.3}'
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```
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| 字段 | 类型 | 说明 |
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|------|------|------|
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| `speed` | float | 目标速度 m/s，正=前进，负=后退 |
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| `steer` | float | 目标转向角 rad，正=左转，负=右转 |
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**Python 客户端示例**：
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```python
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import time
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import requests
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IP = "192.168.1.100"
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# 获取图像
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r = requests.get(f"http://{IP}:8765/image")
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with open("frame.jpg", "wb") as f:
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f.write(r.content)
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# 获取状态
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state = requests.get(f"http://{IP}:8765/state").json()
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print(f"位置: ({state['x']}, {state['y']}), 速度: {state['speed_actual']} m/s")
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# 发送控制指令
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requests.post(f"http://{IP}:8765/cmd", json={"speed": 1.0, "steer": 0.2})
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time.sleep(2)
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requests.post(f"http://{IP}:8765/cmd", json={"speed": 0.0, "steer": 0.0})
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```
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**ROS2 桥接示例**：
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```python
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import rclpy
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from rclpy.node import Node
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from sensor_msgs.msg import Image as RosImage
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from geometry_msgs.msg import Twist
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from cv_bridge import CvBridge
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import requests
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import numpy as np
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import cv2
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IP = "192.168.1.100"
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class OrigincarBridge(Node):
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def __init__(self):
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super().__init__("origincar_bridge")
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self.bridge = CvBridge()
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self.pub = self.create_publisher(RosImage, "/image", 10)
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self.sub = self.create_subscription(Twist, "/cmd_vel", self.cmd_cb, 10)
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self.timer = self.create_timer(0.1, self.fetch_and_publish)
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def fetch_and_publish(self):
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r = requests.get(f"http://{IP}:8765/image", timeout=1)
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if r.status_code == 200:
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arr = np.frombuffer(r.content, np.uint8)
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cv_img = cv2.imdecode(arr, cv2.IMREAD_COLOR)
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msg = self.bridge.cv2_to_imgmsg(cv_img, "bgr8")
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self.pub.publish(msg)
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def cmd_cb(self, msg: Twist):
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requests.post(f"http://{IP}:8765/cmd", json={
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"speed": msg.linear.x,
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"steer": msg.angular.z
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})
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rclpy.init()
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node = OrigincarBridge()
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rclpy.spin(node)
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```
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## 键盘控制
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| 按键 | 方式 | 作用 |
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|------|------|------|
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| W/S | 按住 | 前进/后退 |
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| A/D | 按住 | 左转/右转 |
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| ↑/↓ | 点按 | 速度幅度 ±0.2 m/s（0~2.0） |
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| ←/→ | 点按 | 转向幅度 ±0.05 rad（0~0.5） |
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| Space | 点按 | 截图保存到 `captures/` |
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键盘与 HTTP `/cmd` 可同时使用：按住 W/A/S/D 时键盘优先，松开后自动切回 HTTP 控制。
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## 场景结构
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```
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scene.xml — 5m×5m 地图 + 40cm 白色围栏 + 阿克曼小车
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main.py — 仿真控制 + HTTP API 服务
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origincar.urdf / origincar.xacro — 小车模型（参考）
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```
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