Variation Points

RoboVAST supports plugin-provided variation types. The following are available by default:

General

ParameterVariationList

Creates configurations from a predefined list of parameter values.

Expected parameters:

• name: Name of the parameter to vary

• values: List of values for the parameter

ParameterVariationDistributionUniform

Creates configurations with random parameter values from a uniform distribution.

Expected parameters:

• name: Name of the parameter to vary

• num_variations: Number of configurations to create

• min: Minimum value for the parameter

• max: Maximum value for the parameter

• type: Data type of the parameter (e.g., int, float, string)

• seed: Seed for random number generation to ensure reproducibility

ParameterVariationDistributionGaussian

Creates configurations with random parameter values from a Gaussian (normal) distribution.

Expected parameters:

• name: Name of the parameter to vary

• num_variations: Number of configurations to create

• mean: Mean value for the parameter

• std: Standard deviation for the parameter

• min: Minimum value for the parameter

• max: Maximum value for the parameter

• type: Data type of the parameter (e.g., int, float, string)

• seed: Seed for random number generation to ensure reproducibility

Navigation

FloorplanVariation

Creates floorplan variations from variation files and generates corresponding map and mesh files.

Expected parameters:

• name: List of two parameter names - first for map file, second for mesh file

• variation_files: List of variation files to use for floorplan generation (must contain at least one file)

• num_variations: Number of floorplan variations to generate (minimum 1)

• seed: Seed for random number generation to ensure reproducibility

Generated outputs:

• Map YAML file (maps/*.yaml)

• Map PGM file (maps/*.pgm)

• 3D mesh STL file (3d-mesh/*.stl)

FloorplanGeneration

Generates artifacts (maps and 3D meshes) from existing floorplan files without creating variations. Unlike FloorplanVariation which creates multiple variations from .variation files, this processes .fpm floorplan files directly and generates exactly one configuration per input floorplan.

Expected parameters:

• name: List of two parameter names - first for map file, second for mesh file

• floorplans: List of paths to .fpm floorplan files to generate artifacts for (must contain at least one file)

Generated outputs:

• Map YAML file (maps/*.yaml)

• Map PGM file (maps/*.pgm)

• 3D mesh STL file (3d-mesh/*.stl)

Example configuration:

- FloorplanGeneration:
    name:
    - map_file
    - mesh_file
    floorplans:
    - floorplans/rooms/rooms.fpm
    - floorplans/hallways/hallways.fpm

PathVariationRandom

Generates random navigation paths with multiple waypoints between start and goal poses.

Expected parameters:

• start_pose: Start position as parameter reference (@start_pose) or direct pose with x, y, yaw (in meters and radians)

• goal_poses: Goal positions as parameter reference (@goal_poses or @goal_pose) or list of poses

• num_goal_poses: Number of goal poses to generate per path (determines output parameter: single goal_pose or list goal_poses)

• path_length: Target path length in meters

• num_paths: Number of different paths to generate

• min_distance: Minimum distance between consecutive waypoints in meters

• map_file: Optional map file path (uses scenario default if omitted)

• path_length_tolerance: Acceptable deviation from target path length in meters (default: 0.5)

• seed: Random seed for reproducible generation

• robot_diameter: Robot diameter for collision checking in meters

Behavior:

• Generates sequential waypoints with target distances between them

• Validates path length within specified tolerance

• Automatically detects output parameter name from reference: @goal_pose outputs single pose, @goal_poses outputs list

• Uses path caching for performance optimization

Generated outputs:

• start_pose: Generated or specified start pose

• goal_pose or goal_poses: Generated goal pose(s) depending on reference

• Internal path data for validation and visualization

ObstacleVariation

Places random obstacles in the environment based on configured obstacle types.

Expected parameters:

• name: Name of the parameter to store static objects

• obstacle_configs: List of obstacle configurations, each containing:

  • amount: Number of obstacles to place

  • max_distance: Maximum distance from path (currently not used for random placement)

  • model: Model name/path for the obstacle

  • xacro_arguments: Arguments to pass to xacro for model generation

• seed: Seed for random number generation to ensure reproducibility

• robot_diameter: Diameter of the robot for collision checking

• map_file: Optional map file path (can be omitted if provided by previous variation)

• count: Number of obstacle configurations to generate (default: 1)

Generated outputs:

• List of static objects with spawn poses and model information

PathVariationRasterized

Creates route variations covering all areas of the map using a square grid rasterization. Generates paths between raster points that meet specified path length criteria.

Expected parameters:

• raster_size: Grid spacing between raster points in meters

• path_length: Target path length in meters

• robot_diameter: Robot diameter for collision checking in meters

• start_pose: Optional start position as parameter reference (@start_pose) or direct pose with x, y, yaw. If omitted, all valid raster points are used as potential start poses.

• num_goal_poses: Number of goal poses per path (default: 1). Single goal mode uses grid-to-grid paths; multi-goal mode uses search radius algorithm.

• map_file: Optional map file path (uses scenario default if omitted)

• raster_offset_x: X-axis offset for grid alignment in meters (default: 0.0)

• raster_offset_y: Y-axis offset for grid alignment in meters (default: 0.0)

• path_length_tolerance: Acceptable deviation from target path length in meters (default: 0.5)

Behavior:

• Creates square grid covering entire map area, filtering points in obstacles or too close to walls

• Single goal mode (num_goal_poses: 1): Generates paths from each valid raster point to every other valid raster point for comprehensive coverage testing

• Multi-goal mode (num_goal_poses > 1): Calculates search radius as (path_length / raster_size) / (num_goal_poses + 1) and generates multiple waypoints per path

• Respects robot diameter for collision checking and grid alignment controlled by offsets

Generated outputs:

• start_pose: Start pose (either specified or from raster grid)

• goal_pose or goal_poses: Goal pose(s) depending on num_goal_poses

• Internal path data, raster points, and path length for validation and visualization