Exwayz SLAM algorithm performs a processing pipeline.

Pre processing : aims at reducing the number of input points of the registration algorithm (ICP), mainly discarding troublesome or redundant point from the raw data.

ICP : ICP (Iterative Closest Point) is the registration algorithm used to calculate the relative position of the upcoming frame with respect to the local map, which is constructed at the same time

Map update : Exwayz SLAM maintains and updates an internal local map which is used for the upcoming frame registration. This map is expressed in an internal data structure and has nothing to do with the point cloud produced at the end of the full mapping pipeline.

Default YAML

Below is the example slam.yaml configuration file with all parameters open to the user. The comments are the main documentation of each parameters.

odometry:
    # [optional, default=true] Enable motion compensation using the frames' 
    # timestamps
    enable_motion_compensation: true

    # [optional] Preprocessing settings
    pre_process:
        # [optional, default=2] Number of threads used for pre-processing
        num_threads: 2

        # [optional, default=32] Number of rows for the spherical subsampling
        num_rows : 32
        # [optional, default=512] Number of cols for the spherical subsampling
        num_cols : 512
        # [optional, default=closest] Keep strategy for each pixel
        #   * closest: keep only the point with lowest range in each pixel
        #   * farthest: keep only the point with highest range in each pixel
        #   * both: keep both points with lowest and highest range in each pixel
        keep_strategy : farthest

        # [optional, default=0.2(m)] Minimum range of a point to be preserved 
        # in subsampling
        range_min: 2.0
        # [optional, default=250.0(m)] Maximum range of a point to be preserved 
        # in subsampling
        range_max: 150.0

        # [optional, default=[0.0, 0.0, 0.0](m)] Center of the exclusion 
        # axis-aligned box
        center: [0.0, 0.0, 0.0]
        # [optional, default=[0.0, 0.0, 0.0](m)] Size of the exclusion 
        # axis-aligned box
        size: [5.0, 5.0, 5.0]

        # [optional, default=0.1(m)] Resolution of the final voxel subsampling
        grid_resolution: 0.1

    # [optional] ICP parameters used for initialization
    init:
        # [optional, default=5] Number of frames on which use the following 
        # d_max value
        num_init: 5
        # [optional, default=0.5(m)] Outlier rejection distance
        d_max: 0.5

    # [optional] ICP parameters used for localization
    icp:
        # [optional, default=2] Number of threads used for nearest neighbour 
        # search
        num_threads: 2
        # [optional, default=10] Maximimum number of iterations
        num_iter: 5
        # [optional, default=0.2(m)] Outlier rejection distance
        d_max: 0.2

    # [optional] Map parameters
    map_local:
        # [optional, default=0.5(m)] Linear distance to the last added frame 
        # for triggering map update
        d_update: 0.5
        # [optional, default=200.0(m)] Pruning radius of the map
        d_prune: 200.0
        # [optional, default=30] Number of neighbors used to compute map normals
        normals_knn: 30
        # [optional, default=0.2(m)] Map voxel size
        resolution: 0.2

    # [optional] Checks on input data
    checks:
        # [optional, default=0.7] Rejection ratio used to discard incoming 
        # frames 
        # that have suspiciously low nb of points, e.g. less than 
        # input_rejection_ratio * previous_frame
        input_rejection_ratio: 0.7

    # [optional] Output settings
    output:
        # [optional, default=2] Output point cloud mode
        #   * 0: no output pointcloud
        #   * 1: process (subsampled) point cloud
        #   * 2: full frame
        pc_mode: 1

    # [required] (ros only) ROS parameters
    ros:
        # [optional, default=/exwayz/slam] Output namespace, prepends all 
        # outputs.
        namespace: /exwayz/slam

        # [required] Input PointCloud2 topic
        input_pointcloud2:
            # [required] Topic name
            topic: <topic-name>
            # [optional, default=20] Subscribe queue size
            queue_size: 20

        # [optional] Output Odometry settings
        output_odometry:
            # [optional, default=/odometry] Output topic
            topic: /odometry
            # [optional, default=xyz_map] Odometry message header.frame_id
            parent_frame_id: xyz_map
            # [optional, default=""] Odometry message child_frame_id. If empty, 
            # input PointCloud2 frame id is used
            child_frame_id: slam
            # [optional, default=false] Optionally inverts output pose and 
            # frame_ids
            invert: false
            # [optional, default=false] Publish parent->child TF using the 
            # output Odometry
            publish_tf: true

        # [optional] Output PointCloud2 settings
        output_pointcloud2:
            # [optional, default=/pointcloud2] Output topic
            topic: /pointcloud2
            # [optional, default=""] Output frame id. If empty, input
            # PointCloud2 frame id is used
            frame_id: slam

        # [optional] Output ExwayzStatus settings
        output_status:
            # [optional, default=/status]
            topic: /status

    # [optional] (rtmaps only) RTMaps parameters
    rtmaps:
        # [optional, default=5000(Ko)] Point cloud output buffer size
        pc_buffer_size: 5000

Explanation

enable_motion_compensation

pre_process

icp

map_local

checks

outputs

API-specific I/O parameters

ros

rtmaps