What problem does it solve?
Converting a USD warehouse or facility scene into a 2D occupancy grid that ROS navigation stacks can consume is error-prone: you must decide which prims count as obstacles, filter by height, apply robot-radius buffers, and export the correct PNG/YAML pair. This Skill codifies that entire pipeline.
Core Features & Use Cases
- PhysX-based generation: Use the documented
isaacsim.asset.gen.omap extension via GUI or Python bindings to raycast collision geometry into an occupancy grid.
- Direct USD projection fallback: Traverse USD prims, project XY footprints onto a 2D grid with height filtering, apply dilation buffers with scipy, and export ROS-standard PNG/YAML maps.
- Path planning integration: Load maps into the MobilityGen
OccupancyMap class for A* planning, Nav2 setup, and AMR fleet validation.
- Use Case: You have a 220x180m warehouse USD stage and need a 0.1m/px occupancy map with a 0.5m robot buffer to validate AMR routes in Nav2 before deployment.
Quick Start
Generate a ROS-compatible occupancy map from my USD warehouse scene at 0.1 meter resolution with a 0.5 meter robot buffer.