Add more details on how to run datasets
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README.md
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README.md
@ -37,11 +37,36 @@ An accurate calibration is crucial for successfully running the software. To get
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The filter uses the first 200 IMU messages to initialize the gyro bias, acc bias, and initial orientation. Therefore, the robot is required to start from a stationary state in order to initialize the VIO successfully.
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## Example Usage
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There are launch files prepared for the EuRoC and fast flight dataset separately. Upon launching the `msckf_vio_*.launch`, two ros nodes are created:
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* `image_processor` takes the stereo images to detect and track features.
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* `vio` takes the feature measurements and tightly fuses them with the IMU messages to estimate pose.
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## EuRoC and UPenn Fast flight dataset example usage
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Once the `msckf_vio` is built and sourced (via `source <path to catkin_ws>/devel/setup.bash`), there are two launch files prepared for the [EuRoC](https://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets) and [UPenn fast flight](https://github.com/KumarRobotics/msckf_vio/wiki/Dataset) dataset with launch files `msckf_vio_euroc.launch` and `msckf_vio_fla.launch` respectively. The launch files instanciates two ROS nodes:
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* `image_processor` processes stereo images to detect and track features
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* `vio` obtains feature measurements from the `image_processor` and tightly fuses them with the IMU messages to estimate pose.
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These launch files can be executed via
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```
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roslaunch msckf_vio msckf_vio_euroc.launch
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or
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roslaunch msckf_vio msckf_vio_fla.launch
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```
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Once the nodes are running you need to run the dataset rosbags, for example:
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```
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rosbag play V1_01_easy.bag
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```
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As mentioned in the previous section **The robot is required to start from a stationary state in order to initialize the VIO successfully**
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To visualize the pose and feature estimations you can use the provided rviz configurations found in `msckf_vio/rviz` folder to visualize corresponding datatset estimations (EuRoC: `rviz_euroc_config.rviz`, Fast dataset: `rvis_fla_config.rviz`).
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## ROS Nodes
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### `image_processor` node
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