MoveIt Pro Example Workspace

This simulation-only workspace contains reference materials for using MoveIt Pro, including example robot configurations, simulated environments, and reusable behaviors. Hardware robot configurations, drivers, and hardware-only dependencies are intentionally excluded to reduce build time and avoid maintaining complex dependencies that the simulation examples do not use.

Cloning

Install Git LFS before cloning so robot meshes and scene assets are checked out correctly:

sudo apt install git-lfs
git lfs install
git clone <repo-url>

Robot descriptions and simulation assets are vendored under src/external_dependencies; each vendored source has an UPSTREAM.yaml file recording its repository, commit, and pruned paths. No source submodules are required for simulation.

The moveit_pro_sam2 and moveit_pro_sam3 submodules contain optional perception models used by ML demonstration Objectives. Initialize them only when those Objectives are needed:

git submodule update --init src/moveit_pro_sam2 src/moveit_pro_sam3

Robot Configs

• april_tag_sim
• dual_arm_sim
• factory_sim
• grinding_sim
• hangar_sim
• kitchen_sim
• lab_sim
• lunar_sim
• phoebe_sim
• vla_sim
• moveit_pro_franka_configs/franka_base_config
• moveit_pro_kinova_configs/kinova_gen3_base_config
• moveit_pro_kinova_configs/kinova_sim
• moveit_pro_kinova_configs/space_satellite_sim
• moveit_pro_kinova_configs/space_satellite_sim_camera_cal
• moveit_pro_ur_configs/mock_sim
• moveit_pro_ur_configs/multi_arm_sim
• moveit_pro_ur_configs/picknik_ur_base_config

The hardware-only kinova_gen3_site_config and picknik_ur_site_config configurations are not included. They bring up physical Kinova and Universal Robots hardware, respectively, while the retained base and simulation configurations provide the descriptions and interfaces needed by this workspace.

Updating vendored dependencies

Each UPSTREAM.yaml file under src/external_dependencies records the exact upstream commit and retained paths. Refresh a dependency from that commit, preserve its license files, reapply the documented pruning, and validate every config that consumes the package.

The optional ML model submodules can be advanced independently when their demonstration Objectives need a newer model package.