robotx_ekf

package for extended kalman filter

ros2 run robotx_ekf robotx_ekf_node

have to

• determin dt carefully
• set proper variance
• it has filtering step twice (1. y=CX 2.gps observation)

connect to VRX gazebo

• Firstly, run wamvtan/vrx

docker run -it wamvtan/vrx /bin/bash
ros2 launch vrx_gz competition.launch.py world:=stationkeeping_task headless:=true urdf:=/home/config/wamv_target.urdf

• Next, run another docker_image wamvtan/dev_container which includes our autonomous system.

docker run -it wamvtan/dev_container /bin/bash
ros2 run vrx_bridge vrx_bridge_node
ros2 launch vrx_gz competition.launch.py world:=stationkeeping_task headless:=true urdf:=/home/config/wamv_target.urdf

• if you want to run vrx_gz on you local computer, you don't need to run container.
• And do this command below.you run robotx_ekf_node and geopose_converter and vrx_bridge

ros2 run vrx_bridge vrx_bridge_node
ros2 launch vrx_gz competition.launch.py world:=stationkeeping_task headless:=true urdf:=/home/config/wamv_target.urdf

• you can see /estimated_pose topic