SNP Implementation at Automate 2023

This demo uses a Motoman HC10 mounted on a table with an Intel RealSense camera to reconstruct the surface of an arbitrary part and generate motion plans for polishing parts in a raster pattern

Run

Run the application from a pre-built Docker image using the following commands:

On hardware

cd docker
docker compose up

In simulation

First create the file docker-compose.override.yml in the docker directory with the following content:

services:
  snp_automate_2023:
    environment:
      SNP_SIM_ROBOT: true
      SNP_SIM_VISION: true

Then bring up the application using docker-compose

cd docker
docker compose up

Local build

1. Follow the build setup instructions for the main repository
2. Clone the application-specific ROS2 dependencies into the same workspace

   cd <snp_workspace>
   vcs import src < snp_automate_2023/dependencies.repos
   

3. Build

   colcon build --cmake-args -DTESSERACT_BUILD_FCL=OFF
   

4. Run the application

   cd <snp_workspace>
   source install/setup.bash
   ros2 launch snp_automate_2023 start.launch.xml sim_robot:=<true|false> sim_vision:=<true|false>