无人车传感器自走代码
时间: 2023-07-02 08:12:31 浏览: 125
无人车的自走代码需要根据具体的无人车型号和传感器类型进行编写,以下是一个简单的示例代码,可以使用激光雷达和视觉传感器进行自主导航:
```python
import rospy
from sensor_msgs.msg import LaserScan, Image
from geometry_msgs.msg import Twist
from cv_bridge import CvBridge
import cv2
class SelfDrivingCar:
def __init__(self):
self.bridge = CvBridge()
self.image_sub = rospy.Subscriber('/camera/image_raw', Image, self.image_callback)
self.laser_sub = rospy.Subscriber('/scan', LaserScan, self.laser_callback)
self.cmd_vel_pub = rospy.Publisher('/cmd_vel', Twist, queue_size=1)
def image_callback(self, data):
cv_image = self.bridge.imgmsg_to_cv2(data, 'bgr8')
# 检测路标或标志物,并确定方向
# ...
cmd_vel = Twist()
# 根据方向调整速度和角速度
# ...
self.cmd_vel_pub.publish(cmd_vel)
def laser_callback(self, data):
# 使用激光雷达检测周围的障碍物
# ...
cmd_vel = Twist()
# 根据障碍物的位置和距离调整速度和角速度
# ...
self.cmd_vel_pub.publish(cmd_vel)
if __name__ == '__main__':
rospy.init_node('self_driving_car')
car = SelfDrivingCar()
rospy.spin()
```
在上面的代码中,`SelfDrivingCar` 类初始化时订阅了两个主题:`/camera/image_raw` 和 `/scan`。在 `image_callback` 中,将图像数据转换为 OpenCV 格式,并使用视觉算法来检测路标或标志物,并根据检测结果调整车辆的速度和角速度。在 `laser_callback` 中,使用激光雷达检测周围的障碍物,并根据障碍物的位置和距离调整车辆的速度和角速度。最后,将调整后的速度和角速度发布到 `/cmd_vel` 主题上,控制无人车的运动。
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