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Copy file name to clipboardExpand all lines: docs/CHANGELOG.md
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# What's new
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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).
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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).
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### Jan 2022
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### November, 2018
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* Added Weather Effects and [APIs](apis.md#weather-apis)
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* Added [Time of Day API](apis.md#time-of-day-api)
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* 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).
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* 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).
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*[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)
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* Highly efficient [NoDisplay view mode](settings.md#viewmode) to turn off main screen rendering so you can capture images at high rate
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*[Enable/disable sensors](https://github.com/Microsoft/AirSim/pull/1479) via settings
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*[Character Control APIs](https://github.com/Microsoft/AirSim/blob/master/PythonClient/airsim/client.py#L137) (works on TalkingHeads binaries in release)
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*[Character Control APIs](https://github.com/Microsoft/AirSim/blob/main/PythonClient/airsim/client.py#L137) (works on TalkingHeads binaries in release)
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*[Arducopter Solo Support](https://github.com/Microsoft/AirSim/pull/1387)
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*[Linux install without sudo access](https://github.com/Microsoft/AirSim/pull/1434)
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*[Kinect like ROS publisher](https://github.com/Microsoft/AirSim/pull/1298)
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
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
[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.
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[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.
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[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.
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[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.
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Finally, the details about how temperatures were estimated for plants and animals in the Africa environment, etc. can be found in this paper:
* 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.
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* 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.
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* Details of the AirSim C++ and Python APIs are [here](apis.md).
Copy file name to clipboardExpand all lines: docs/adding_new_apis.md
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To add the RPC code to call the new API, follow the steps below. Follow the implementation of other APIs defined in the files.
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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.
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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.
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2. Add the C++ client API method in [RpcClientBase.cpp](https://github.com/microsoft/AirSim/blob/master/AirLib/src/api/RpcLibClientBase.cpp)
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2. Add the C++ client API method in [RpcClientBase.cpp](https://github.com/microsoft/AirSim/blob/main/AirLib/src/api/RpcLibClientBase.cpp)
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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)
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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)
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## Testing
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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 -
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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.
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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.
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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.
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Add `import setup_path` before `import airsim` in your files. Now the latest master API (or any branch currently checked out) will be used.
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Add `import setup_path` before `import airsim` in your files. Now the latest main API (or any branch currently checked out) will be used.
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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.
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.
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.
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.
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#### Services:
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A Dockerfile is present in the [`tools`](https://github.com/microsoft/AirSim/tree/master/tools/Dockerfile-ROS) directory. To build the `airsim-ros` image -
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A Dockerfile is present in the [`tools`](https://github.com/microsoft/AirSim/tree/main/tools/Dockerfile-ROS) directory. To build the `airsim-ros` image -
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.
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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.
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