Merge pull request microsoft#4596 from jonyMarino/change_master_to_main

Change master to main in docs

docs/CHANGELOG.md

@@ -1,6 +1,6 @@
 # What's new
 
-Below is summarized list of important changes. This does not include minor/less important changes or bug fixes or documentation update. This list updated every few months. For complete detailed changes, please review [commit history](https://github.com/Microsoft/AirSim/commits/master).
+Below is summarized list of important changes. This does not include minor/less important changes or bug fixes or documentation update. This list updated every few months. For complete detailed changes, please review [commit history](https://github.com/Microsoft/AirSim/commits/main).
 
 
 ### Jan 2022
@@ -180,7 +180,7 @@ Below is summarized list of important changes. This does not include minor/less
 ### November, 2018
 * Added Weather Effects and [APIs](apis.md#weather-apis)
 * Added [Time of Day API](apis.md#time-of-day-api)
-* An experimental integration of [AirSim on Unity](https://github.com/Microsoft/AirSim/tree/master/Unity) is now available. Learn more in [Unity blog post](https://blogs.unity3d.com/2018/11/14/airsim-on-unity-experiment-with-autonomous-vehicle-simulation). 
+* An experimental integration of [AirSim on Unity](https://github.com/Microsoft/AirSim/tree/main/Unity) is now available. Learn more in [Unity blog post](https://blogs.unity3d.com/2018/11/14/airsim-on-unity-experiment-with-autonomous-vehicle-simulation). 
 * [New environments](https://github.com/Microsoft/AirSim/releases/tag/v1.2.1): Forest, Plains (windmill farm), TalkingHeads (human head simulation), TrapCam (animal detection via camera)
 * Highly efficient [NoDisplay view mode](settings.md#viewmode) to turn off main screen rendering so you can capture images at high rate
 * [Enable/disable sensors](https://github.com/Microsoft/AirSim/pull/1479) via settings
@@ -191,7 +191,7 @@ Below is summarized list of important changes. This does not include minor/less
 * [Custom speed units](https://github.com/Microsoft/AirSim/pull/1181)
 * [ROS publisher](https://github.com/Microsoft/AirSim/pull/1135)
 * [simSetObjectPose API](https://github.com/Microsoft/AirSim/pull/1161)
-* [Character Control APIs](https://github.com/Microsoft/AirSim/blob/master/PythonClient/airsim/client.py#L137) (works on TalkingHeads binaries in release)
+* [Character Control APIs](https://github.com/Microsoft/AirSim/blob/main/PythonClient/airsim/client.py#L137) (works on TalkingHeads binaries in release)
 * [Arducopter Solo Support](https://github.com/Microsoft/AirSim/pull/1387)
 * [Linux install without sudo access](https://github.com/Microsoft/AirSim/pull/1434)
 * [Kinect like ROS publisher](https://github.com/Microsoft/AirSim/pull/1298)

docs/CONTRIBUTING.md

@@ -13,5 +13,5 @@
 - Keep your pull request small, ideally under 10 files.
 - Make sure you don't include large binary files.
 - When adding new includes, make dependency is absolutely necessary.
-- Rebase your branch frequently with master (once every 2-3 days is ideal).
+- Rebase your branch frequently with main (once every 2-3 days is ideal).
 - Make sure your code would compile on Windows, Linux and OSX.

docs/InfraredCamera.md

@@ -3,12 +3,12 @@ This is a tutorial for generating simulated thermal infrared (IR) images using A
 Pre-compiled Africa Environment can be downloaded from the Releases tab of this Github repo: 
 [Windows Pre-compiled binary](https://github.com/Microsoft/AirSim/releases/tag/v1.2.1)
 
-To generate your own data, you may use two python files: [create_ir_segmentation_map.py](https://github.com/Microsoft/AirSim/tree/master/PythonClient//computer_vision/create_ir_segmentation_map.py) and 
-[capture_ir_segmentation.py](https://github.com/Microsoft/AirSim/tree/master/PythonClient//computer_vision/capture_ir_segmentation.py).
+To generate your own data, you may use two python files: [create_ir_segmentation_map.py](https://github.com/Microsoft/AirSim/tree/main/PythonClient//computer_vision/create_ir_segmentation_map.py) and 
+[capture_ir_segmentation.py](https://github.com/Microsoft/AirSim/tree/main/PythonClient//computer_vision/capture_ir_segmentation.py).
 
-[create_ir_segmentation_map.py](https://github.com/Microsoft/AirSim/tree/master/PythonClient//computer_vision/create_ir_segmentation_map.py) uses temperature, emissivity, and camera response information to estimate the thermal digital count that could be expected for the objects in the environment, and then reassigns the segmentation IDs in AirSim to match these digital counts. It should be run before starting to capture thermal IR data. Otherwise, digital counts in the IR images will be incorrect. The camera response, temperature, and emissivity data are all included for the Africa environment.
+[create_ir_segmentation_map.py](https://github.com/Microsoft/AirSim/tree/main/PythonClient//computer_vision/create_ir_segmentation_map.py) uses temperature, emissivity, and camera response information to estimate the thermal digital count that could be expected for the objects in the environment, and then reassigns the segmentation IDs in AirSim to match these digital counts. It should be run before starting to capture thermal IR data. Otherwise, digital counts in the IR images will be incorrect. The camera response, temperature, and emissivity data are all included for the Africa environment.
 
-[capture_ir_segmentation.py](https://github.com/Microsoft/AirSim/tree/master/PythonClient//computer_vision/capture_ir_segmentation.py) is run after the segmentation IDs have been reassigned. It tracks objects of interest and records the infrared and scene images from the multirotor. It uses Computer Vision mode.
+[capture_ir_segmentation.py](https://github.com/Microsoft/AirSim/tree/main/PythonClient//computer_vision/capture_ir_segmentation.py) is run after the segmentation IDs have been reassigned. It tracks objects of interest and records the infrared and scene images from the multirotor. It uses Computer Vision mode.
 
 Finally, the details about how temperatures were estimated for plants and animals in the Africa environment, etc. can be found in this paper:
 

docs/Unity.md

@@ -118,7 +118,7 @@ chmod +x "{project_name}.{configuration}"
 ./{project_name}.{configuration}
 ```
 ### Using Airsim API
-* For quickstart with the Python APIs for the car or the drone, simply run the [`hello_car.py`](https://github.com/Microsoft/AirSim/blob/master/PythonClient/car/hello_car.py) or the [`hello_drone.py`](https://github.com/Microsoft/AirSim/blob/master/PythonClient/multirotor/hello_drone.py) script accordingly. 
+* For quickstart with the Python APIs for the car or the drone, simply run the [`hello_car.py`](https://github.com/Microsoft/AirSim/blob/main/PythonClient/car/hello_car.py) or the [`hello_drone.py`](https://github.com/Microsoft/AirSim/blob/main/PythonClient/multirotor/hello_drone.py) script accordingly. 
 * Details of the AirSim C++ and Python APIs are [here](apis.md). 
 
 ### Acknowledgements

docs/adding_new_apis.md

@@ -32,19 +32,19 @@ The APIs use [msgpack-rpc protocol](https://github.com/msgpack-rpc/msgpack-rpc)
 
 To add the RPC code to call the new API, follow the steps below. Follow the implementation of other APIs defined in the files.
 
-1. Add an RPC handler in the server which calls your implemented method in [RpcLibServerBase.cpp](https://github.com/microsoft/AirSim/blob/master/AirLib/src/api/RpcLibServerBase.cpp). Vehicle-specific APIs are in their respective vehicle subfolder.
+1. Add an RPC handler in the server which calls your implemented method in [RpcLibServerBase.cpp](https://github.com/microsoft/AirSim/blob/main/AirLib/src/api/RpcLibServerBase.cpp). Vehicle-specific APIs are in their respective vehicle subfolder.
 
-2. Add the C++ client API method in [RpcClientBase.cpp](https://github.com/microsoft/AirSim/blob/master/AirLib/src/api/RpcLibClientBase.cpp)
+2. Add the C++ client API method in [RpcClientBase.cpp](https://github.com/microsoft/AirSim/blob/main/AirLib/src/api/RpcLibClientBase.cpp)
 
-3. Add the Python client API method in [client.py](https://github.com/microsoft/AirSim/blob/master/PythonClient/airsim/client.py). If needed, add or modify a structure definition in [types.py](https://github.com/microsoft/AirSim/blob/master/PythonClient/airsim/types.py)
+3. Add the Python client API method in [client.py](https://github.com/microsoft/AirSim/blob/main/PythonClient/airsim/client.py). If needed, add or modify a structure definition in [types.py](https://github.com/microsoft/AirSim/blob/main/PythonClient/airsim/types.py)
 
 ## Testing
 
 Testing is required to ensure that the API is working as expected. For this, as expected, you'll have to use the source-built AirSim and Blocks environment. Apart from this, if using the Python APIs, you'll have to use the `airsim` package from source rather than the PyPI package. Below are 2 ways described to go about using the package from source -
 
-1. Use [setup_path.py](https://github.com/microsoft/AirSim/blob/master/PythonClient/multirotor/setup_path.py). It will setup the path such that the local airsim module is used instead of the pip installed package. This is the method used in many of the scripts since the user doesn't need to do anything other than run the script.
+1. Use [setup_path.py](https://github.com/microsoft/AirSim/blob/main/PythonClient/multirotor/setup_path.py). It will setup the path such that the local airsim module is used instead of the pip installed package. This is the method used in many of the scripts since the user doesn't need to do anything other than run the script.
     Place your example script in one of the folders inside `PythonClient` like `multirotor`, `car`, etc. You can also create one to keep things separate, and copy the `setup_path.py` file from another folder.
-    Add `import setup_path` before `import airsim` in your files. Now the latest master API (or any branch currently checked out) will be used.
+    Add `import setup_path` before `import airsim` in your files. Now the latest main API (or any branch currently checked out) will be used.
 
 2. Use a [local project pip install](https://pip.pypa.io/en/stable/cli/pip_install/#local-project-installs). Regular install would create a copy of the current source and use it, whereas Editable install (`pip install -e .` from inside the `PythonClient` folder) would change the package whenever the Python API files are changed. Editable install has the benefit when working on several branches or API is not finalized.
 

docs/airsim_ros_pkgs.md

@@ -76,7 +76,7 @@ Let's look at the ROS API for both nodes:
 
 #### Publishers:
 
-- `/airsim_node/origin_geo_point` [airsim_ros_pkgs/GPSYaw](https://github.com/microsoft/AirSim/tree/master/ros/src/airsim_ros_pkgs/msg/GPSYaw.msg)
+- `/airsim_node/origin_geo_point` [airsim_ros_pkgs/GPSYaw](https://github.com/microsoft/AirSim/tree/main/ros/src/airsim_ros_pkgs/msg/GPSYaw.msg)
 GPS coordinates corresponding to global NED frame. This is set in the airsim's [settings.json](https://microsoft.github.io/AirSim/settings/) file under the `OriginGeopoint` key.
 
 - `/airsim_node/VEHICLE_NAME/global_gps` [sensor_msgs/NavSatFix](https://docs.ros.org/api/sensor_msgs/html/msg/NavSatFix.html)
@@ -92,7 +92,7 @@ Odometry in NED frame (default name: odom_local_ned, launch name and frame type
 
 - `/tf` [tf2_msgs/TFMessage](https://docs.ros.org/api/tf2_msgs/html/msg/TFMessage.html)
 
-- `/airsim_node/VEHICLE_NAME/altimeter/SENSOR_NAME` [airsim_ros_pkgs/Altimeter](https://github.com/microsoft/AirSim/blob/master/ros/src/airsim_ros_pkgs/msg/Altimeter.msg)
+- `/airsim_node/VEHICLE_NAME/altimeter/SENSOR_NAME` [airsim_ros_pkgs/Altimeter](https://github.com/microsoft/AirSim/blob/main/ros/src/airsim_ros_pkgs/msg/Altimeter.msg)
 This the current altimeter reading for altitude, pressure, and [QNH](https://en.wikipedia.org/wiki/QNH)
 
 - `/airsim_node/VEHICLE_NAME/imu/SENSOR_NAME` [sensor_msgs::Imu](http://docs.ros.org/api/sensor_msgs/html/msg/Imu.html)
@@ -109,20 +109,20 @@ IMU sensor data
 
 #### Subscribers:
 
-- `/airsim_node/vel_cmd_body_frame` [airsim_ros_pkgs/VelCmd](https://github.com/microsoft/AirSim/tree/master/ros/src/airsim_ros_pkgs/msg/VelCmd.msg)
+- `/airsim_node/vel_cmd_body_frame` [airsim_ros_pkgs/VelCmd](https://github.com/microsoft/AirSim/tree/main/ros/src/airsim_ros_pkgs/msg/VelCmd.msg)
   Ignore `vehicle_name` field, leave it to blank. We will use `vehicle_name` in future for multiple drones.
 
-- `/airsim_node/vel_cmd_world_frame` [airsim_ros_pkgs/VelCmd](https://github.com/microsoft/AirSim/tree/master/ros/src/airsim_ros_pkgs/msg/VelCmd.msg)
+- `/airsim_node/vel_cmd_world_frame` [airsim_ros_pkgs/VelCmd](https://github.com/microsoft/AirSim/tree/main/ros/src/airsim_ros_pkgs/msg/VelCmd.msg)
   Ignore `vehicle_name` field, leave it to blank. We will use `vehicle_name` in future for multiple drones.
 
-- `/gimbal_angle_euler_cmd` [airsim_ros_pkgs/GimbalAngleEulerCmd](https://github.com/microsoft/AirSim/tree/master/ros/src/airsim_ros_pkgs/msg/GimbalAngleEulerCmd.msg)
+- `/gimbal_angle_euler_cmd` [airsim_ros_pkgs/GimbalAngleEulerCmd](https://github.com/microsoft/AirSim/tree/main/ros/src/airsim_ros_pkgs/msg/GimbalAngleEulerCmd.msg)
   Gimbal set point in euler angles.
 
-- `/gimbal_angle_quat_cmd` [airsim_ros_pkgs/GimbalAngleQuatCmd](https://github.com/microsoft/AirSim/tree/master/ros/src/airsim_ros_pkgs/msg/GimbalAngleQuatCmd.msg)
+- `/gimbal_angle_quat_cmd` [airsim_ros_pkgs/GimbalAngleQuatCmd](https://github.com/microsoft/AirSim/tree/main/ros/src/airsim_ros_pkgs/msg/GimbalAngleQuatCmd.msg)
   Gimbal set point in quaternion.
 
-- `/airsim_node/VEHICLE_NAME/car_cmd` [airsim_ros_pkgs/CarControls](https://github.com/microsoft/AirSim/blob/master/ros/src/airsim_ros_pkgs/msg/CarControls.msg)
-Throttle, brake, steering and gear selections for control. Both automatic and manual transmission control possible, see the [`car_joy.py`](https://github.com/microsoft/AirSim/blob/master/ros/src/airsim_ros_pkgs/scripts/car_joy) script for use.
+- `/airsim_node/VEHICLE_NAME/car_cmd` [airsim_ros_pkgs/CarControls](https://github.com/microsoft/AirSim/blob/main/ros/src/airsim_ros_pkgs/msg/CarControls.msg)
+Throttle, brake, steering and gear selections for control. Both automatic and manual transmission control possible, see the [`car_joy.py`](https://github.com/microsoft/AirSim/blob/main/ros/src/airsim_ros_pkgs/scripts/car_joy) script for use.
 
 #### Services:
 
@@ -197,24 +197,24 @@ Throttle, brake, steering and gear selections for control. Both automatic and ma
 
 #### Services:
 
-- `/airsim_node/VEHICLE_NAME/gps_goal` [Request: [srv/SetGPSPosition](https://github.com/microsoft/AirSim/blob/master/ros/src/airsim_ros_pkgs/srv/SetGPSPosition.srv)]
+- `/airsim_node/VEHICLE_NAME/gps_goal` [Request: [srv/SetGPSPosition](https://github.com/microsoft/AirSim/blob/main/ros/src/airsim_ros_pkgs/srv/SetGPSPosition.srv)]
   Target gps position + yaw.
   In **absolute** altitude.
 
-- `/airsim_node/VEHICLE_NAME/local_position_goal` [Request: [srv/SetLocalPosition](https://github.com/microsoft/AirSim/blob/master/ros/src/airsim_ros_pkgs/srv/SetLocalPosition.srv)]
+- `/airsim_node/VEHICLE_NAME/local_position_goal` [Request: [srv/SetLocalPosition](https://github.com/microsoft/AirSim/blob/main/ros/src/airsim_ros_pkgs/srv/SetLocalPosition.srv)]
   Target local position + yaw in global NED frame.
 
 #### Subscribers:
 
-- `/airsim_node/origin_geo_point` [airsim_ros_pkgs/GPSYaw](https://github.com/microsoft/AirSim/tree/master/ros/src/airsim_ros_pkgs/msg/GPSYaw.msg)
+- `/airsim_node/origin_geo_point` [airsim_ros_pkgs/GPSYaw](https://github.com/microsoft/AirSim/tree/main/ros/src/airsim_ros_pkgs/msg/GPSYaw.msg)
   Listens to home geo coordinates published by `airsim_node`.
 
 - `/airsim_node/VEHICLE_NAME/odom_local_ned` [nav_msgs/Odometry](https://docs.ros.org/api/nav_msgs/html/msg/Odometry.html)
   Listens to odometry published by `airsim_node`
 
 #### Publishers:
 
-- `/vel_cmd_world_frame` [airsim_ros_pkgs/VelCmd](https://github.com/microsoft/AirSim/tree/master/ros/src/airsim_ros_pkgs/msg/VelCmd.msg)
+- `/vel_cmd_world_frame` [airsim_ros_pkgs/VelCmd](https://github.com/microsoft/AirSim/tree/main/ros/src/airsim_ros_pkgs/msg/VelCmd.msg)
   Sends velocity command to `airsim_node`
 
 #### Global params
@@ -298,7 +298,7 @@ roslaunch airsim_ros_pkgs rviz.launch
 
 ### Using Docker for ROS
 
-A Dockerfile is present in the [`tools`](https://github.com/microsoft/AirSim/tree/master/tools/Dockerfile-ROS) directory. To build the `airsim-ros` image -
+A Dockerfile is present in the [`tools`](https://github.com/microsoft/AirSim/tree/main/tools/Dockerfile-ROS) directory. To build the `airsim-ros` image -
 
 ```shell
 cd tools

docs/airsim_tutorial_pkgs.md

@@ -1,7 +1,7 @@
 # AirSim ROS Tutorials
 
 This is a set of sample AirSim `settings.json`s, roslaunch and rviz files to give a starting point for using AirSim with ROS.     
-See [airsim_ros_pkgs](https://github.com/microsoft/AirSim/blob/master/ros/src/airsim_ros_pkgs/README.md) for the ROS API.
+See [airsim_ros_pkgs](https://github.com/microsoft/AirSim/blob/main/ros/src/airsim_ros_pkgs/README.md) for the ROS API.
 
 
 ## Setup
@@ -26,7 +26,7 @@ catkin build airsim_tutorial_pkgs -DCMAKE_C_COMPILER=gcc-8 -DCMAKE_CXX_COMPILER=
 ## Examples
 
 ### Single drone with monocular and depth cameras, and lidar
- - Settings.json - [front_stereo_and_center_mono.json](https://github.com/microsoft/AirSim/blob/master/ros/src/airsim_tutorial_pkgs/settings/front_stereo_and_center_mono.json)
+ - Settings.json - [front_stereo_and_center_mono.json](https://github.com/microsoft/AirSim/blob/main/ros/src/airsim_tutorial_pkgs/settings/front_stereo_and_center_mono.json)
  ```shell
  $ source PATH_TO/AirSim/ros/devel/setup.bash
  $ roscd airsim_tutorial_pkgs
@@ -40,11 +40,11 @@ catkin build airsim_tutorial_pkgs -DCMAKE_C_COMPILER=gcc-8 -DCMAKE_CXX_COMPILER=
  $ source PATH_TO/AirSim/ros/devel/setup.bash
  $ roslaunch airsim_tutorial_pkgs front_stereo_and_center_mono.launch
  ```
- The above would start rviz with tf's, registered RGBD cloud using [depth_image_proc](https://wiki.ros.org/depth_image_proc) using the [`depth_to_pointcloud` launch file](https://github.com/microsoft/AirSim/blob/master/ros/src/airsim_tutorial_pkgs/launch/front_stereo_and_center_mono/depth_to_pointcloud.launch), and the lidar point cloud. 
+ The above would start rviz with tf's, registered RGBD cloud using [depth_image_proc](https://wiki.ros.org/depth_image_proc) using the [`depth_to_pointcloud` launch file](https://github.com/microsoft/AirSim/blob/main/ros/src/airsim_tutorial_pkgs/launch/front_stereo_and_center_mono/depth_to_pointcloud.launch), and the lidar point cloud. 
 
 
 ### Two drones, with cameras, lidar, IMU each
-- Settings.json - [two_drones_camera_lidar_imu.json](https://github.com/microsoft/AirSim/blob/master/ros/src/airsim_tutorial_pkgs/settings/two_drones_camera_lidar_imu.json) 
+- Settings.json - [two_drones_camera_lidar_imu.json](https://github.com/microsoft/AirSim/blob/main/ros/src/airsim_tutorial_pkgs/settings/two_drones_camera_lidar_imu.json) 
 
  ```shell
  $ source PATH_TO/AirSim/ros/devel/setup.bash
@@ -59,7 +59,7 @@ catkin build airsim_tutorial_pkgs -DCMAKE_C_COMPILER=gcc-8 -DCMAKE_CXX_COMPILER=
 You can view the tfs in rviz. And do a `rostopic list` and `rosservice list` to inspect the services avaiable.    
 
 ### Twenty-five drones in a square pattern
-- Settings.json - [twenty_five_drones.json](https://github.com/microsoft/AirSim/blob/master/ros/src/airsim_tutorial_pkgs/settings/twenty_five_drones.json) 
+- Settings.json - [twenty_five_drones.json](https://github.com/microsoft/AirSim/blob/main/ros/src/airsim_tutorial_pkgs/settings/twenty_five_drones.json) 
 
  ```shell
  $ source PATH_TO/AirSim/ros/devel/setup.bash