317 lines
8.2 KiB
Markdown
317 lines
8.2 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, "y": -2.3, "z": 0.08, "yaw_deg": 0.0,
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"vx": 0.98, "vy": 0.0, "wx": 0.0, "wy": 0.0, "wz": 0.01,
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"speed_target": 1.0, "speed_actual": 0.98, "steer_target": 0.0,
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"speed_amp": 1.0, "steer_amp": 0.35
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}
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```
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### GET `/scan`
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模拟 LSLIDAR N10 2D 激光雷达（360°, 450 点）。
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```bash
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curl http://{IP}:8765/scan
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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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"angle_min": -3.14, "angle_max": 3.14, "angle_increment": 0.014,
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"range_min": 0.15, "range_max": 3.0,
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"ranges": [0.52, 0.51, 0.53, ...]
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}
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```
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### GET `/odom`
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里程计数据（匹配 `nav_msgs/Odometry`）。
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```bash
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curl http://{IP}:8765/odom
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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, "y": -2.3, "yaw": 3.14,
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"vx": 0.98, "vy": 0.0, "wz": 0.01,
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"orientation": {"w": 0.0, "x": 0.0, "y": 0.0, "z": 1.0}
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}
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```
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### GET `/power`
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电池电压（模拟 12V）。
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```bash
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curl http://{IP}:8765/power
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# → {"voltage": 12.0}
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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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**Ackermann 模式**：
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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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**差速模式**（兼容 `cmd_vel/Twist`）：
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| 字段 | 类型 | 说明 |
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|------|------|------|
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| `vx` | float | 线速度 m/s |
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| `vy` | float | 横向速度 m/s（忽略） |
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| `wz` | float | 角速度 rad/s，自动转为转向角 |
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```bash
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# 差速模式
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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 '{"vx": 1.0, "wz": 0.5}'
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```
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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**（仿真机 HTTP → ROS2 局域网）：
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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, Imu, LaserScan
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from nav_msgs.msg import Odometry
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from geometry_msgs.msg import Twist, Quaternion
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from std_msgs.msg import Float32
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import requests, math, numpy as np, 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.pub_scan = self.create_publisher(LaserScan, "/scan", 10)
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self.pub_odom = self.create_publisher(Odometry, "/odom", 10)
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self.pub_imu = self.create_publisher(Imu, "/imu/data_raw", 10)
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self.pub_pwr = self.create_publisher(Float32, "/PowerVoltage", 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(0.033, self.sync) # ~30Hz
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def sync(self):
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# LaserScan
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data = requests.get(f"http://{IP}:8765/scan", timeout=1).json()
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msg = LaserScan()
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msg.header.frame_id = "laser"; msg.header.stamp = self.get_clock().now().to_msg()
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msg.angle_min = data["angle_min"]; msg.angle_max = data["angle_max"]
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msg.angle_increment = data["angle_increment"]
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msg.range_min = data["range_min"]; msg.range_max = data["range_max"]
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msg.ranges = data["ranges"]
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self.pub_scan.publish(msg)
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# Odometry
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odom = requests.get(f"http://{IP}:8765/odom", timeout=1).json()
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o = Odometry()
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o.header.frame_id = "odom"; o.child_frame_id = "base_link"
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o.pose.pose.position.x = odom["x"]; o.pose.pose.position.y = odom["y"]
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o.pose.pose.orientation = Quaternion(**odom["orientation"])
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o.twist.twist.linear.x = odom["vx"]; o.twist.twist.angular.z = odom["wz"]
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self.pub_odom.publish(o)
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# IMU
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imu_d = requests.get(f"http://{IP}:8765/imu", timeout=1).json()
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imu = Imu()
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imu.header.frame_id = "gyro_link"
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imu.orientation = Quaternion(**imu_d["orientation"])
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imu.angular_velocity.x = imu_d["angular_velocity"]["x"]
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imu.angular_velocity.y = imu_d["angular_velocity"]["y"]
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imu.angular_velocity.z = imu_d["angular_velocity"]["z"]
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imu.linear_acceleration.x = imu_d["linear_acceleration"]["x"]
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imu.linear_acceleration.y = imu_d["linear_acceleration"]["y"]
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imu.linear_acceleration.z = imu_d["linear_acceleration"]["z"]
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self.pub_imu.publish(imu)
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# Power
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p = Float32(data=requests.get(f"http://{IP}:8765/power", timeout=1).json()["voltage"])
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self.pub_pwr.publish(p)
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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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"vx": msg.linear.x, "wz": 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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## 锥桶编辑器
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可视化在地图上放置锥桶，保存到 `cones.json`，仿真启动时自动加载。
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```bash
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uv run python cone_editor.py
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```
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| 操作 | 说明 |
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|------|------|
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| 左键点击地图 | 放置锥桶 |
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| 右键点击地图 | 删除最近锥桶 |
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| 鼠标移动 | 查看世界坐标 |
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| 保存按钮 | 写入 `cones.json` |
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地图为 5m×5m，左下角 (-2.5, -2.5)，右上角 (2.5, 2.5)。
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`cones.json` 格式：
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```json
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[
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{"x": -1.45, "y": -2.29},
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{"x": -0.06, "y": -1.56},
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{"x": 1.82, "y": -0.91}
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]
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```
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也可直接编辑此文件增删锥桶。
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## 场景结构
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```
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scene.xml — 场景描述（地图 + 围栏 + 小车，锥桶动态注入）
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main.py — 仿真控制 + HTTP API 服务
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cone_editor.py — 锥桶可视化编辑器
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cones.json — 锥桶位置配置
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cone.obj — 锥体网格（底20cm→顶5cm，高27cm）
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cone_white.obj — 白色反光条网格
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origincar.urdf / origincar.xacro — 小车模型（参考）
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```
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