Docs: move links to relative paths

docs/howto/how_to_add_a_new_lidar_driver.md

@@ -10,17 +10,17 @@ As default, Apollo platform support multiple types of Lidar drivers, including 1
 
 Taking velodyne lidar driver as an example, there are three major components:
 
-1. [Driver](https://github.com/ApolloAuto/apollo/tree/master/modules/drivers/velodyne/driver): Driver receives UDP data packets from lidar sensor, and packages the data packets into a frame of scanning data in the format of VelodyneScan. VelodyneScan is defined in file below:
+1. [Driver](../../modules/drivers/velodyne/driver): Driver receives UDP data packets from lidar sensor, and packages the data packets into a frame of scanning data in the format of VelodyneScan. VelodyneScan is defined in file below:
 ```
 modules/drivers/velodyne/proto/velodyne.proto
 ```
 
-2. [Parser](https://github.com/ApolloAuto/apollo/tree/master/modules/drivers/velodyne/parser): Parser takes one frame data in format of VelodyneScan as input, converts the cloud points in the frame from spherical coordinate system to Cartesian coordinates system, then sends out the point cloud as output. The pointcloud format is defined in file below:
+2. [Parser](../../modules/drivers/velodyne/parser): Parser takes one frame data in format of VelodyneScan as input, converts the cloud points in the frame from spherical coordinate system to Cartesian coordinates system, then sends out the point cloud as output. The pointcloud format is defined in file below:
 ```
 modules/drivers/proto/pointcloud.proto
 ```
 
-3. [Compensator](https://github.com/ApolloAuto/apollo/tree/master/modules/drivers/velodyne/compensator): Compensator takes pointcloud data and pose data as inputs. Based on the corresponding pose information for each cloud point, it converts each cloud point information aligned with the latest time in the current lidar scan frame, minimizing the motion error due the movement of the vehicle. Thus, each cloud point needs carry its own timestamp information.
+3. [Compensator](../../modules/drivers/velodyne/compensator): Compensator takes pointcloud data and pose data as inputs. Based on the corresponding pose information for each cloud point, it converts each cloud point information aligned with the latest time in the current lidar scan frame, minimizing the motion error due the movement of the vehicle. Thus, each cloud point needs carry its own timestamp information.
 
 ## Steps to add a new Lidar driver
 

docs/howto/how_to_add_a_new_lidar_driver_cn.md

@@ -3,11 +3,11 @@ Lidar是一种常用的环境感知传感器，利用脉冲激光来照射目标
 
 ## Velodyne驱动的主要部分
 
-1. [Driver](https://github.com/ApolloAuto/apollo/tree/master/modules/drivers/velodyne/driver): 通过网络端口接收lidar硬件产生的UDP数据包，将每一帧封装成VelodyneScan格式后发送。
+1. [Driver](../../modules/drivers/velodyne/driver): 通过网络端口接收lidar硬件产生的UDP数据包，将每一帧封装成VelodyneScan格式后发送。
 
-2. [Parser](https://github.com/ApolloAuto/apollo/tree/master/modules/drivers/velodyne/parser): 接收VelodyneScan数据，把VelodyneScan中的点由球面坐标系转换成空间直角坐标系下的pointcldoud点云格式后发送。
+2. [Parser](../../modules/drivers/velodyne/parser): 接收VelodyneScan数据，把VelodyneScan中的点由球面坐标系转换成空间直角坐标系下的pointcldoud点云格式后发送。
 
-3. [Compensator](https://github.com/ApolloAuto/apollo/tree/master/modules/drivers/velodyne/compensator): 接收点云数据和pose数据，根据每个点的对应的pose信息把点转换到点云中最大时刻对应的坐标系下，减小由车辆自身的运动带来的误差。需要点云数据中包含每个点的时间戳信息。
+3. [Compensator](../../modules/drivers/velodyne/compensator): 接收点云数据和pose数据，根据每个点的对应的pose信息把点转换到点云中最大时刻对应的坐标系下，减小由车辆自身的运动带来的误差。需要点云数据中包含每个点的时间戳信息。
 
 
 

docs/howto/how_to_run_offline_perception_visualizer.md

@@ -7,7 +7,7 @@ We introduce the detailed steps to build and run the offline visualizer in docke
 Before running the visualizer, we need to prepare necessary PCD and Pose data which can be extracted from a ROS bag with recorded point cloud data. To facilitate the data extraction, we provide a ROS launch file to dump the PCD frame file and a python script to generate the Pose file for each frame.
 
 #### 1.1 Launching the PCD exporter
- Additional details can be found in the [Velodyne driver doc](https://github.com/ApolloAuto/apollo/tree/master/modules/drivers/velodyne)
+ Additional details can be found in the [Velodyne driver doc](../../modules/drivers/velodyne)
 ```
 roslaunch velodyne export_pcd_offline.launch
 ```

docs/howto/how_to_run_offline_perception_visualizer_cn.md

@@ -7,7 +7,7 @@ DreamView工具可以模拟感知模块并展现模拟效果，但它缺乏可
 在运行可视化工具之前，我们需要准备必要的PCD和Pose数据，这些数据可以从带有记录点云数据的ROS包中提取。为了便于数据提取，我们提供了一个ROS启动文件来转储PCD帧文件和一个python脚本来为每个帧生成Pose文件。
 
 #### 1.1 启动PCD导出器
- 更多详细信息请参考 [Velodyne驱动文档](https://github.com/ApolloAuto/apollo/tree/master/modules/drivers/velodyne)
+ 更多详细信息请参考 [Velodyne驱动文档](../../modules/drivers/velodyne)
 ```
 roslaunch velodyne export_pcd_offline.launch
 ```

docs/howto/how_to_tune_control_parameters.md

@@ -43,7 +43,7 @@ The longitudinal controller is configured as a cascaded PID + Calibration table.
 ## Controller Tuning
 
 ### Useful tools
-Tool like [diagnostics](https://github.com/ApolloAuto/apollo/tree/master/modules/tools/diagnostics) and [realtime_plot](https://github.com/ApolloAuto/apollo/tree/master/modules/tools/realtime_plot) are useful for controller tuning and can be found under `apollo/modules/tools/`.
+Tool like [diagnostics](../../modules/tools/diagnostics) and [realtime_plot](../../modules/tools/realtime_plot) are useful for controller tuning and can be found under `apollo/modules/tools/`.
 ### Lateral Controller Tuning
 The lateral controller is designed for minimal tuning effort.  The basic lateral controller tuning steps for *all* vehicles are:
 

docs/howto/how_to_tune_control_parameters_cn.md

@@ -42,7 +42,7 @@
 ## 控制器调谐
 
 ### 实用工具
-类似于[诊断](https://github.com/ApolloAuto/apollo/tree/master/modules/tools/diagnostics) 和 [realtime_plot](https://github.com/ApolloAuto/apollo/tree/master/modules/tools/realtime_plot) 可用于控制器调优，并且可以在`apollo/modules/tools/`中找到.
+类似于[诊断](../../modules/tools/diagnostics) 和 [realtime_plot](../../modules/tools/realtime_plot) 可用于控制器调优，并且可以在`apollo/modules/tools/`中找到.
 ### 横向控制器的整定
 横向控制器设计用于最小调谐力。“所有”车辆的基础横向控制器调谐步骤如下：