问一个精准的问题借助CatGPT等AI助手得到需要的帮助-以ROS机器人为例
问一个精准的问题借助CatGPT等AI助手得到需要的帮助-以ROS机器人为例
为什么写这一篇？
动机：之前学生或网上的朋友，问各类机器人问题，”遇到报错了，没调出来，帮我看看吧？“
我通常看不懂问题，也无法帮忙，毕竟加班太多了，实在抱歉。
问题其实具体一些，比如遇到xxx样的报错，具体xxx没有调出来这样更为合适。
之前，靠精准搜索来寻求自己遇到问题的答案，现在这种方式依然适用。
但是随着ChatGPT的成功，如果精准提问，其实此类AI应用也可以大幅提升学习效果或解决问题的效率。
AI指出：相比于搜索引擎，ChatGPT的优势在于它可以进行更加智能化的交互式对话，能够根据用户的提问进行更加精准的回答。同时，ChatGPT还可以进行自我学习和优化，不断提高回答的准确性和质量。不足之处在于，ChatGPT的回答可能会受到模型训练数据的限制，无法涵盖所有的知识领域和问题类型。此外，ChatGPT的回答也可能存在一定的主观性和误差，需要用户进行判断和筛选。
看如下案例：
回答特别敷衍，甩出官网完事，那如果具体一些呢？
ROS kinetic详细安装步骤：
AI答复：
我可以回答这个问题。首先，你需要在Ubuntu 16.04上安装ROS Kinetic。你可以按照以下步骤进行安装： 添加ROS源 在终端中输入以下命令： sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list' 添加ROS key 在终端中输入以下命令： sudo apt-key adv --keyserver hkp://ha.pool.sks-keyservers.net:80 --recv-key 421C365BD9FF1F717815A3895523BAEEB01FA116 更新软件包 在终端中输入以下命令： sudo apt-get update 安装ROS Kinetic 在终端中输入以下命令： sudo apt-get install ros-kinetic-desktop-full 初始化ROS 在终端中输入以下命令： sudo rosdep init rosdep update 设置环境变量 在终端中输入以下命令： echo "source /opt/ros/kinetic/setup.bash" >> ~/.bashrc source ~/.bashrc 安装ROS工具 在终端中输入以下命令： sudo apt-get install python-rosinstall python-rosinstall-generator python-wstool build-essential 安装完成后，你就可以开始使用ROS Kinetic了。
在linux系统安装ROS2 humble的详细步骤？
你可以在终端中输入以下命令来安装ROS2 Humble：
添加ROS2 Humble软件源：
sudo apt update && sudo apt install curl gnupg2 lsb-release
curl -s https://raw.githubusercontent.com/ros/rosdistro/master/ros.asc | sudo apt-key add -
sudo sh -c 'echo "deb [arch=amd64,arm64] http://packages.ros.org/ros2/ubuntu $(lsb_release -cs) main" > /etc/apt/sources.list.d/ros2-latest.list'
安装ROS2 Humble：
sudo apt update
sudo apt install ros-humble-desktop
初始化ROS2 Humble：
source /opt/ros/humble/setup.bash
创建ROS2工作空间：
mkdir -p ~/ros2_ws/src
cd ~/ros2_ws/src
构建ROS2工作空间：
cd ~/ros2_ws
colcon build
source ~/ros2_ws/install/setup.bash
现在，你已经成功安装了ROS2 Humble，并创建了一个ROS2工作空间。
复杂一些的问题呢？
turtlesim中键盘遥控机器人运动的详细步骤？
AI：
首先，打开终端，输入命令“roscore”启动ROS核心。然后，在新的终端中输入命令“rosrun turtlesim turtlesim_node”启动turtlesim节点。接下来，打开新的终端，输入命令“rosrun turtlesim turtle_teleop_key”启动键盘遥控节点。此时，你可以使用键盘上的方向键来控制机器人的运动。按下“Ctrl + C”可以停止节点的运行。
turtlesim实现贪吃蛇的详细步骤？
AI：
首先，需要安装turtlesim软件包。然后，打开终端并输入以下命令：
rosrun turtlesim turtlesim_node
这将启动turtlesim节点。接下来，创建一个新的ROS软件包并添加一个名为“snake”的节点。在该节点中，使用ROS消息来控制turtle的运动。使用ROS订阅器来接收键盘输入，并使用ROS发布器来控制turtle的运动。最后，将snake节点与turtlesim节点连接起来，以便在turtlesim中显示贪吃蛇游戏。
具体的步骤可以参考ROS官方文档或者相关教程。
https://blog.csdn.net/zhangrelay/article/details/124238177
import rospy
from tanksim.msg import Pose
from tanksim.srv import Spawn
from tanksim.srv import SetPen
from geometry_msgs.msg import Twist
from geometry_msgs.msg import TransformStamped
import random
import math
tank1_pose = Pose()
tanklist = []
lasttank = 1
nexttankIndex = 1
class mySpawner:
def __init__(self, tname):
self.tank_name = tname
self.state = 1
rospy.wait_for_service('/spawn')
try:
client = rospy.ServiceProxy('/spawn', Spawn)
x = random.randint(1, 10)
y = random.randint(1, 10)
theta = random.uniform(1, 3.14)
name = tname
_nm = client(x, y, theta, name)
rospy.loginfo("tank Created [%s] [%f] [%f]", name, x, y)
rospy.Subscriber(self.tank_name + '/pose', Pose, self.tank_poseCallback)
self.pub = rospy.Publisher(self.tank_name + '/cmd_vel', Twist, queue_size=10)
self.tank_to_follow = 1
self.tank_pose = Pose()
rospy.wait_for_service("/" + tname + '/set_pen')
try:
client = rospy.ServiceProxy("/" + tname + '/set_pen', SetPen)
client(0,0,0,0,1)
except rospy.ServiceException as e:
print("Service call failed: %s"%e)
except rospy.ServiceException as e:
print("Service tp spawn a tank failed. %s", e)
def tank_poseCallback(self, data):
self.tank_pose = data
def tank_velocity(self, msg):
self.pub.publish(msg)
def tank1_poseCallback(data):
global tank1_pose
global lasttank
global tanklist
global nexttankIndex
tank1_pose.x = round(data.x, 4)
tank1_pose.y = round(data.y, 4)
tank1_pose.theta = round(data.theta, 4)
for i in range(len(tanklist)):
twist_data = Twist()
diff = math.sqrt(pow((tank1_pose.x - tanklist[i].tank_pose.x) , 2) + pow((tank1_pose.y - tanklist[i].tank_pose.y), 2))
ang = math.atan2(tank1_pose.y - tanklist[i].tank_pose.y, tank1_pose.x - tanklist[i].tank_pose.x) - tanklist[i].tank_pose.theta
if(ang <= -3.14) or (ang > 3.14):
ang = ang / math.pi
if (tanklist[i].state == 1):
if diff < 1.0:
tanklist[i].state = 2
tanklist[i].tank_to_follow = lasttank
lasttank = i + 2
rospy.loginfo("tank Changed [%s] [%f] [%f]", tanklist[i].tank_name, diff, ang)
nexttankIndex += 1
tanklist.append(mySpawner("tank" + str(nexttankIndex)))
else:
parPose = tank1_pose
if(tanklist[i].tank_to_follow != 1):
parPose = tanklist[tanklist[i].tank_to_follow - 2].tank_pose
diff = math.sqrt(pow((parPose.x - tanklist[i].tank_pose.x) , 2) + pow((parPose.y - tanklist[i].tank_pose.y), 2))
goal = math.atan2(parPose.y - tanklist[i].tank_pose.y, parPose.x - tanklist[i].tank_pose.x)
ang = math.atan2(math.sin(goal - tanklist[i].tank_pose.theta), math.cos(goal - tanklist[i].tank_pose.theta))
if(ang <= -3.14) or (ang > 3.14):
ang = ang / (2*math.pi)
if(diff < 0.8):
twist_data.linear.x = 0
twist_data.angular.z = 0
else:
twist_data.linear.x = 2.5 * diff
twist_data.angular.z = 20 * ang
tanklist[i].tank_velocity(twist_data)
tanklist[i].oldAngle = ang
def spawn_tank_fn():
global nexttankIndex
rospy.init_node('snake_tank', anonymous=True)
rospy.Subscriber('/tank1/pose', Pose, tank1_poseCallback)
rospy.wait_for_service("/tank1/set_pen")
try:
client = rospy.ServiceProxy('/tank1/set_pen', SetPen)
client(0,0,0,0,1)
except rospy.ServiceException as e:
print("Service call failed: %s"%e)
nexttankIndex += 1
tanklist.append(mySpawner("tank" + str(nexttankIndex)))
# for i in range(2,10):
# tanklist.append(mySpawner("tank" + str(i)))
rospy.spin()
if __name__ == "__main__":
spawn_tank_fn()
AI给出的案例不太可靠。
turtlesim实现贪吃蛇的Python代码
import rospy
from geometry_msgs.msg import Twist
from turtlesim.msg import Pose
from math import pow, atan2, sqrt
class TurtleBot:
def __init__(self):
rospy.init_node('turtlebot_controller', anonymous=True)
self.velocity_publisher = rospy.Publisher('/turtle1/cmd_vel', Twist, queue_size=10)
self.pose_subscriber = rospy.Subscriber('/turtle1/pose', Pose, self.update_pose)
self.pose = Pose()
self.rate = rospy.Rate(10)
def update_pose(self, data):
self.pose = data
self.pose.theta = round(self.pose.theta, 4)
def euclidean_distance(self, goal_pose):
return sqrt(pow((goal_pose.x - self.pose.x), 2) + pow((goal_pose.y - self.pose.y), 2))
def linear_vel(self, goal_pose, constant=1.5):
return constant * self.euclidean_distance(goal_pose)
def steering_angle(self, goal_pose):
return atan2(goal_pose.y - self.pose.y, goal_pose.x - self.pose.x)
def angular_vel(self, goal_pose, constant=6):
return constant * (self.steering_angle(goal_pose) - self.pose.theta)
def move2goal(self):
goal_pose = Pose()
goal_pose.x = input("Set your x goal: ")
goal_pose.y = input("Set your y goal: ")
distance_tolerance = input("Set your tolerance: ")
vel_msg = Twist()
while self.euclidean_distance(goal_pose) >= distance_tolerance:
vel_msg.linear.x = self.linear_vel(goal_pose)
vel_msg.linear.y = 0
vel_msg.linear.z = 0
vel_msg.angular.x = 0
vel_msg.angular.y = 0
vel_msg.angular.z = self.angular_vel(goal_pose)
self.velocity_publisher.publish(vel_msg)
self.rate.sleep()
vel_msg.linear.x = 0
vel_msg.angular.z = 0
self.velocity_publisher.publish(vel_msg)
if __name__ == '__main__':
try:
x = TurtleBot()
x.move2goal()
except rospy.ROSInterruptException:
pass