## AUTOGENERATED DON'T DELETE
## CategoryPackage
<<PackageHeader(mcl3d)>> <<TOC(4)>>

== Overview ==
This package contains one single node: `mcl3d_node`, which estimates robot localization based on incoming visual odometry, 3D point clouds, radio-based measurements and a 3D map of the environment, fused into a Monte Carlo Localization (MCL) algorithm.

== Tf tree ==
The transforms tree (following [[http://www.ros.org/reps/rep-0105.html|REP 105]]) is as follows:

 . `map` → `odom` → `base_link` → `camera`

Visual odometry algorithms generally calculate'' camera motion'' with respect to an initial reference frame `odom`.To be able to calculate ''robot motion'' based on ''camera motion'',  the transformation from the camera frame to the robot frame has to be  known. Therefore this implementation needs to know the tf `base_link` → `camera`  and the tf `odom` → `base_link` to be able to publish map → `odom` in order to correct odometry drift. The node currently uses default values from the sensor setup on the !AscTec Neo Research platform.

== Nodes ==
{{{#!clearsilver CS/NodeAPI
name = viodom_node
desc = This node takes in a stereo pair of images and IMU data, and outputs pose estimates. Images are rectified using calibration information. On startup, an IMU filter needs to be initialized.
sub{
  0.name= left_cam/image_raw
  0.type= sensor_msgs/Image
  0.desc= Left camera raw image.
  1.name= left_cam/camera_info
  1.type= sensor_msgs/CameraInfo
  1.desc= Left camera calibration information.
  2.name= right_cam/image_raw
  2.type= sensor_msgs/Image
  2.desc= Right camera raw image.
  3.name= right_cam/camera_info
  3.type= sensor_msgs/CameraInfo
  3.desc= Right camera calibration information.
  4.name= imu_topic
  4.type= sensor_msgs/Imu
  4.desc= IMU topic.
}
pub{
  0.name= viodom_transform
  0.type= geometry_msgs/TransformStamped
  0.desc= Robot's estimated pose in the odom frame.
  1.name= point_cloud
  1.type= sensor_msgs/PointCloud2
  1.desc= 3D point cloud based on the input stereo pair.
  2.name= tf
  2.type= tf/tfMessage
  2.desc= Publishes the transform from odom to base_link.
}
}}}
== Citing ==
If you use viodom in an academic context, please cite the following publication: http://ieeexplore.ieee.org/document/7502653/

{{{
@INPROCEEDINGS{7502653,
  author={F. J. Perez-Grau and F. R. Fabresse and F. Caballero and A. Viguria and A. Ollero},
  booktitle={2016 International Conference on Unmanned Aircraft Systems (ICUAS)},
  title={Long-term aerial robot localization based on visual odometry and radio-based ranging},
  year={2016},
  pages={608-614},
  doi={10.1109/ICUAS.2016.7502653},
  month={June},}
}}}