* update doc

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diff --git a/docs/doc/en/projects/line_tracking_robot.md b/docs/doc/en/projects/line_tracking_robot.md
@@ -1,5 +1,70 @@
 ---
 title: MaixPy Line Tracking Robot (/Car)
+update:
+  - date: 2024-05-09
+    author: lxowalle
+    version: 1.0.0
+    content: Initial documentation
 ---
 
+Before reading this article, make sure you know how to develop with MaixCAM. For details, please read [Quick Start](../README.md).
+
+## Introduction
+
+This article describes how to implement a line tracking robot using MaixPy.
+
+## How to implement line tracking robot using MaixPy
+
+1. Preparation of MaixCAM and trolley
+2. Implementing the line tracking function
+3. Implement the trolley control function
+
+### Preparation of MaixCAM and trolley
+
+TODO
+
+### Implementing the line tracking function
+
+You can quickly find straight lines using the `get_regression` of the `image` module, see [Line tracking](. /line_tracking.md).
+
+Code：
+
+```python
+from maix import camera, display, image
+
+cam = camera.Camera(320, 240)
+disp = display.Display()
+
+# thresholds = [[0, 80, 40, 80, 10, 80]]      # red
+thresholds = [[0, 80, -120, -10, 0, 30]]    # green
+# thresholds = [[0, 80, 30, 100, -120, -60]]  # blue
+
+while 1:
+    img = cam.read()
+
+    lines = img.get_regression(thresholds, area_threshold = 100)
+    for a in lines:
+        img.draw_line(a.x1(), a.y1(), a.x2(), a.y2(), image.COLOR_GREEN, 2)
+        theta = a.theta()
+        rho = a.rho()
+        if theta > 90:
+            theta = 270 - theta
+        else:
+            theta = 90 - theta
+        img.draw_string(0, 0, "theta: " + str(theta) + ", rho: " + str(rho), image.COLOR_BLUE)
+
+    disp.show(img)
+
+```
+
+The above code implements the function of finding a straight line, note:
+
+- Use `a.theta()` to get the angle of the line.
+- Use `a.rho()` to get the distance between the line and the origin (the origin is in the upper left corner).
+
+After find the straight line with reference to the above code, you can use `a.theta()` and `a.rho()` to control the direction of the cart.
+
+### Implement the trolley control function
+
+TODO
 
diff --git a/docs/doc/en/vision/apriltag.md b/docs/doc/en/vision/apriltag.md
@@ -7,7 +7,7 @@ update:
     content: Initial documentation
 ---
 
-Before reading this article, make sure you are familiar with how to develop with MaixPy. For more details, please read [MaixVision -- MaixPy Programming + Graphical Block Programming](../basic/maixvision.md).
+Before reading this article, make sure you are familiar with how to develop with MaixCAM. For more details, please read [Quick Start](../README.md).
 
 ## Introduction
 

diff --git a/docs/doc/en/vision/find_blobs.md b/docs/doc/en/vision/find_blobs.md
@@ -10,7 +10,7 @@ update:
     version: 1.0.1
     content: Added detailed usage for finding blobs
 ---
-Before reading this article, make sure you know how to develop with MaixPy. For details, please read [MaixVision -- MaixPy Programming + Graphical Block Programming](../basic/maixvision.md).
+Before reading this article, make sure you know how to develop with MaixCAM. For details, please read [Quick Start](../README.md).
 
 ## Introduction
 

diff --git a/docs/doc/en/vision/line_tracking.md b/docs/doc/en/vision/line_tracking.md
@@ -8,7 +8,7 @@ update:
 ---
 
 
-Before reading this article, make sure you already know how to develop MaixPy. For details, please read [MaixVision -- MaixPy Programming + Graphical Block Programming](../basic/maixvision.md).
+Before reading this article, make sure you already know how to develop MaixCAM. For details, please read [Quick Start](../README.md).
 
 ## Introduction
 
@@ -37,19 +37,20 @@ disp = display.Display()
 thresholds = [[0, 80, -120, -10, 0, 30]] # green
 # thresholds = [[0, 80, 30, 100, -120, -60]] # blue
 
-while 1.
+while 1:
     img = cam.read()
 
     lines = img.get_regression(thresholds, area_threshold = 100)
-    for a in lines.
+    for a in lines:
         img.draw_line(a.x1(), a.y1(), a.x2(), a.y2(), image.COLOR_GREEN, 2)
         theta = a.theta()
-        if theta > 90.
+        rho = a.rho()
+        if theta > 90:
             theta = 270 - theta
-        if theta > 90: theta = 270 - theta
+        else:
             theta = 90 - theta
-        img.draw_string(0, 0, ‘theta: ’ + str(theta), image.COLOR_BLUE)
-    
+        img.draw_string(0, 0, "theta: " + str(theta) + ", rho: " + str(rho), image.COLOR_BLUE)
+
     disp.show(img)
 ```
 
@@ -71,30 +72,31 @@ Steps:
 3. Get the image from the camera and display it
 
    ```python
-   while 1.
+   while 1:
        img = cam.read()
        disp.show(img)
    ```
 
 4. Call the `get_regression` method to find the straight line in the camera image and draw it to the screen
 
-   ``` python
-   lines = img.get_regression(thresholds, pixels_threshold = 100)
-   for a in lines.
-       img.draw_line(a.x1(), a.y1(), a.x2(), a.y2(), image.COLOR_GREEN, 2)
-       theta = a.theta()
-       if theta > 90.
-           theta = 270 - theta
-       if theta > 90: theta = 270 - theta
-           theta = 90 - theta
-       img.draw_string(0, 0, ‘theta: ’ + str(theta), image.COLOR_BLUE)
+   ```python
+   lines = img.get_regression(thresholds, area_threshold = 100)
+   for a in lines:
+      img.draw_line(a.x1(), a.y1(), a.x2(), a.y2(), image.COLOR_GREEN, 2)
+      theta = a.theta()
+      rho = a.rho()
+      if theta > 90:
+         theta = 270 - theta
+      else:
+         theta = 90 - theta
+      img.draw_string(0, 0, "theta: " + str(theta) + ", rho: " + str(rho), image.COLOR_BLUE)
    ```
 
    - `img` is the camera image read via `cam.read()`, when initialised as `cam = camera.Camera(320, 240)`, the `img` object is an RGB image with a resolution of 320x240.
    - `img.get_regression` is used to find straight lines, `thresholds` is a list of colour thresholds, each element is a colour threshold, multiple thresholds are passed in if multiple thresholds are found at the same time, and each colour threshold has the format `[L_MIN, L_MAX, A_MIN, A_MAX, B_MIN, B_MAX]`, where ` L`, `A`, `B` are the three channels of `LAB` colour space, `L` channel is the luminance, `A` channel is the red-green channel, `B` channel is the blue-yellow channel. `pixels_threshold` is a pixel area threshold used to filter some unwanted straight lines.
    - `for a in lines` is used to iterate through the returned `Line` objects, where `a` is the current `Line` object. Normally the `get_regression` function will only return one `Line` object, but if you need to find more than one line, try the `find_line` method.
    - Use `img.draw_line` to draw the found line, `a.x1(), a.y1(), a.x2(), a.y2()` represent the coordinates of the ends of the line.
-   - Use `img.draw_string` to show the angle between the line and the x-axis in the upper left corner, and `a.theta()` is the angle between the line and the y-axis, which is converted to `theta` for easier understanding.
+   - Use `img.draw_string` to show the angle between the line and the x-axis in the upper left corner, and `a.theta()` is the angle between the line and the y-axis, which is converted to `theta` for easier understanding, `a.rho()` is the length of the vertical line from the origin to the line.
 
 5. Run the code through the maixvision, you can find the line, look at the effect!
 

diff --git a/docs/doc/en/vision/qrcode.md b/docs/doc/en/vision/qrcode.md
@@ -7,7 +7,7 @@ update:
     content: Initial document
 ---
 
-Before reading this article, make sure you are familiar with how to develop with MaixPy. For details, please read [MaixVision -- MaixPy Programming + Graphical Block Programming](../basic/maixvision.md)
+Before reading this article, make sure you are familiar with how to develop with MaixCAM. For details, please read [Quick Start](../README.md).
 
 ## Introduction
 

diff --git a/docs/doc/zh/projects/line_tracking_robot.md b/docs/doc/zh/projects/line_tracking_robot.md
@@ -1,5 +1,71 @@
 ---
 title: MaixPy 小车巡线
+update:
+  - date: 2024-05-09
+    author: lxowalle
+    version: 1.0.0
+    content: 初版文档
 ---
 
+阅读本文前，确保已经知晓如何开发MaixCAM，详情请阅读[快速开始](../README.md)
 
+## 简介
+
+本文将介绍如何使用MaixPy实现寻线小车
+
+## 如何使用MaixPy实现寻线小车
+
+1. 准备MaixCAM与小车
+2. 实现寻线功能
+3. 实现小车控制功能
+
+### 准备MaixCAM与小车
+
+TODO
+
+### 实现寻线功能
+
+使用`image`模块的`get_regression`可以快速寻找到直线，详情见[寻找直线](./line_tracking.md)
+
+代码实现：
+
+```python
+from maix import camera, display, image
+
+cam = camera.Camera(320, 240)
+disp = display.Display()
+
+# thresholds = [[0, 80, 40, 80, 10, 80]]      # red
+thresholds = [[0, 80, -120, -10, 0, 30]]    # green
+# thresholds = [[0, 80, 30, 100, -120, -60]]  # blue
+
+while 1:
+    img = cam.read()
+
+    lines = img.get_regression(thresholds, area_threshold = 100)
+    for a in lines:
+        img.draw_line(a.x1(), a.y1(), a.x2(), a.y2(), image.COLOR_GREEN, 2)
+        theta = a.theta()
+        rho = a.rho()
+        if theta > 90:
+            theta = 270 - theta
+        else:
+            theta = 90 - theta
+        img.draw_string(0, 0, "theta: " + str(theta) + ", rho: " + str(rho), image.COLOR_BLUE)
+
+    disp.show(img)
+
+```
+
+上述代码实现了寻线功能， 上述参数中需注意：
+
+- 设置合适的thresholds值来寻找到对应的直线
+- 设置合适的area_threshold值来过滤环境干扰，可以过滤一些面积小的直线
+- 使用`a.theta()`获取直线的角度
+- 使用`a.rho()`获取直线与原点(原点在左上角)的距离
+
+根据实际环境调试好寻线参数后， 就可以利用`a.theta()`和`a.rho()`控制小车方向了。
+
+### 实现小车控制功能
+
+TODO
diff --git a/docs/doc/zh/vision/apriltag.md b/docs/doc/zh/vision/apriltag.md
@@ -7,7 +7,7 @@ update:
     content: 初版文档
 ---
 
-阅读本文前，确保已经知晓如何开发MaixPy，详情请阅读[MaixVision -- MaixPy 编程 + 图形化积木编程](../basic/maixvision.md)
+阅读本文前，确保已经知晓如何开发MaixCAM，详情请阅读[快速开始](../README.md)
 
 ## 简介
 

diff --git a/docs/doc/zh/vision/find_blobs.md b/docs/doc/zh/vision/find_blobs.md
@@ -11,7 +11,7 @@ update:
     content: 添加寻找色块的详细用法
 ---
 
-阅读本文前，确保已经知晓如何开发MaixPy，详情请阅读[MaixVision -- MaixPy 编程 + 图形化积木编程](../basic/maixvision.md)
+阅读本文前，确保已经知晓如何开发MaixCAM，详情请阅读[快速开始](../README.md)
 
 ## 简介
 

diff --git a/docs/doc/zh/vision/line_tracking.md b/docs/doc/zh/vision/line_tracking.md
@@ -7,15 +7,15 @@ update:
     content: 初版文档
 ---
 
-阅读本文前，确保已经知晓如何开发MaixPy，详情请阅读[MaixVision -- MaixPy 编程 + 图形化积木编程](../basic/maixvision.md)
+阅读本文前，确保已经知晓如何开发MaixCAM，详情请阅读[快速开始](../README.md)
 
 ## 简介
 
 在视觉应用中，在巡迹小车、巡线机器人等应用中经常需要寻找线条的功能。本文将介绍:
 
-- 如何使用MaixPy来寻找直线
+- 如何使用MaixPy来实现巡线功能
 
-- 如何使用MaixCam的默认应用程序寻找直线
+- 如何使用MaixCam的默认应用程序巡线
 
 
 ## 如何使用MaixPy来寻找直线
@@ -43,14 +43,14 @@ while 1:
     for a in lines:
         img.draw_line(a.x1(), a.y1(), a.x2(), a.y2(), image.COLOR_GREEN, 2)
         theta = a.theta()
+        rho = a.rho()
         if theta > 90:
             theta = 270 - theta
         else:
             theta = 90 - theta
-        img.draw_string(0, 0, "theta: " + str(theta), image.COLOR_BLUE)
+        img.draw_string(0, 0, "theta: " + str(theta) + ", rho: " + str(rho), image.COLOR_BLUE)
 
     disp.show(img)
-
 ```
 
 步骤：
@@ -79,22 +79,23 @@ while 1:
 4. 调用`get_regression`方法寻找摄像头图片中的直线，并画到屏幕上
 
    ```python
-   lines = img.get_regression(thresholds, pixels_threshold = 100)
+   lines = img.get_regression(thresholds, area_threshold = 100)
    for a in lines:
-       img.draw_line(a.x1(), a.y1(), a.x2(), a.y2(), image.COLOR_GREEN, 2)
-       theta = a.theta()
-       if theta > 90:
-           theta = 270 - theta
-       else:
-           theta = 90 - theta
-       img.draw_string(0, 0, "theta: " + str(theta), image.COLOR_BLUE)
+      img.draw_line(a.x1(), a.y1(), a.x2(), a.y2(), image.COLOR_GREEN, 2)
+      theta = a.theta()
+      rho = a.rho()
+      if theta > 90:
+         theta = 270 - theta
+      else:
+         theta = 90 - theta
+      img.draw_string(0, 0, "theta: " + str(theta) + ", rho: " + str(rho), image.COLOR_BLUE)
    ```
 
    - `img`是通过`cam.read()`读取到的摄像头图像，当初始化的方式为`cam = camera.Camera(320, 240)`时，`img`对象是一张分辨率为320x240的RGB图。
    - `img.get_regression`用来寻找直线， `thresholds` 是一个颜色阈值列表，每个元素是一个颜色阈值，同时找到多个阈值就传入多个，每个颜色阈值的格式为 `[L_MIN, L_MAX, A_MIN, A_MAX, B_MIN, B_MAX]`，这里的 `L`、`A`、`B` 是`LAB`颜色空间的三个通道，`L` 通道是亮度，`A` 通道是红绿通道，`B` 通道是蓝黄通道。`pixels_threshold`是一个像素面积的阈值，用来过滤一些不需要直线。
    - `for a in lines`用来遍历返回的`Line`对象， 其中`a`就是当前的`Line`对象。通常`get_regression`函数只会返回一个`Line`对象，如果需要寻找多条直线，可以尝试使用`find_line`方法
    - 使用`img.draw_line`来画出找到的线条，`a.x1(), a.y1(), a.x2(), a.y2()`分别代表直线两端的坐标
-   - 使用`img.draw_string`在左上角显示直线与x轴的夹角， `a.theta()`是直线与y轴的夹角， 这里为了方便理解转换成直线与x轴的夹角`theta`
+   - 使用`img.draw_string`在左上角显示直线与x轴的夹角， `a.theta()`是直线与y轴的夹角， 这里为了方便理解转换成直线与x轴的夹角`theta`，`a.rho()`是原点与直线的垂线的长度.
 
 5. 通过maixvision运行代码，就可以寻线啦，看看效果吧
 

diff --git a/docs/doc/zh/vision/qrcode.md b/docs/doc/zh/vision/qrcode.md
@@ -7,7 +7,7 @@ update:
     content: 初版文档
 ---
 
-阅读本文前，确保已经知晓如何开发MaixPy，详情请阅读[MaixVision -- MaixPy 编程 + 图形化积木编程](../basic/maixvision.md)
+阅读本文前，确保已经知晓如何开发MaixCAM，详情请阅读[快速开始](../README.md)
 
 ## 简介
 

diff --git a/examples/vision/image_basic/line_tracking.py b/examples/vision/image_basic/line_tracking.py
@@ -14,10 +14,11 @@
     for a in lines:
         img.draw_line(a.x1(), a.y1(), a.x2(), a.y2(), image.COLOR_GREEN, 2)
         theta = a.theta()
+        rho = a.rho()
         if theta > 90:
             theta = 270 - theta
         else:
             theta = 90 - theta
-        img.draw_string(0, 0, "theta: " + str(theta), image.COLOR_BLUE)
+        img.draw_string(0, 0, "theta: " + str(theta) + ", rho: " + str(rho), image.COLOR_BLUE)
 
-    disp.show(img)
+    disp.show(img)