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10 changes: 5 additions & 5 deletions README.md
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Expand Up @@ -12,13 +12,13 @@ DLIO is a new lightweight LiDAR-inertial odometry algorithm with a novel coarse-
## Instructions

### Sensor Setup
DLIO has been extensively tested using a variety of sensor configurations and currently supports Ouster, Velodyne, and Hesai LiDARs. The point cloud should be of input type `sensor_msgs::PointCloud2` and the 6-axis IMU input type of `sensor_msgs::Imu`.
DLIO has been extensively tested using a variety of sensor configurations and currently supports Ouster, Velodyne, and Hesai LiDARs. The point cloud should have an input type of `sensor_msgs::PointCloud2` and a 6-axis IMU input type of `sensor_msgs::Imu`.

For best performance, extrinsic calibration between the LiDAR/IMU sensors and the robot's center-of-gravity should be inputted into `cfg/dlio.yaml`. If the exact values of these are unavailable, a rough LiDAR-to-IMU extrinsics can also be used (note however that performance will be degraded).
For best performance, extrinsic calibration between the LiDAR/IMU sensors and the robot's center-of-gravity should be inputted into `cfg/dlio.yaml`. If the exact values of these are unavailable, a rough LiDAR-to-IMU extrinsic can also be used (note, however, that performance will be degraded).

IMU intrinsics are also necessary for best performance, and there are several open-source calibration tools to get these values. These values should also go into `cfg/dlio.yaml`. In practice however, if you are just testing this work, using the default ideal values and performing the initial calibration procedure should be fine.
IMU intrinsics are also necessary for best performance, and there are several open-source calibration tools to get these values. These values should also go into `cfg/dlio.yaml`. In practice, however, if you are testing this work, using the default ideal values and performing the initial calibration procedure should be fine.

Also note that the LiDAR and IMU sensors _need_ to be properly time-synchronized, otherwise DLIO will not work. We recommend using a LiDAR with an integrated IMU (such as an Ouster) for simplicity of extrinsics and synchronization.
Also, it is worth to point out that the LiDAR and IMU sensors _need_ to be properly time-synchronized. Otherwise, DLIO will not work. We recommend using a LiDAR with an integrated IMU (such as an Ouster) for simplicity of extrinsic parameters and synchronization.

### Dependencies
The following has been verified to be compatible, although other configurations may work too:
Expand All @@ -32,7 +32,7 @@ The following has been verified to be compatible, although other configurations
- Eigen >= `3.3.7`

```sh
sudo apt install libomp-dev libpcl-dev libeigen3-dev
sudo apt install libomp-dev libpcl-dev libeigen3-dev ros-humble-pcl-ros
```

DLIO currently supports `ROS 1` and `ROS 2`!
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