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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