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State validator based on 3-D grid map

Since R2020b


    The validatorOccupancyMap3D object validates states and discretized motions based on occupancy values in a 3-D occupancy map. The object interprets obstacle-free map locations as valid states. The object interprets occupied and unknown map locations as invalid states.



    validator = validatorOccupancyMap3D creates a 3-D occupancy map validator associated with an SE(3) state space with default settings.


    validator = validatorOccupancyMap3D(stateSpace) creates a validator in the specified state space. The stateSpace input sets the value of the StateSpace property.

    validator = validatorOccupancyMap3D(stateSpace,Name,Value) sets Properties using one or more name-value pairs. Unspecified properties have default values. Enclose each property name in quotes.

    For example, validatorOccupancyMap3D('ValidationDistance',0.1) creates a 3-D occupancy map validator with a sampling interval of 0.1.


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    This property is read-only.

    State space for validating states, specified as a subclass of nav.StateSpace. These are the predefined state space objects:

    Example: validatorOccupancyMap3D(stateSpaceSE3)

    Map used for validating states, specified as an occupancyMap3D object.

    Example: validator.Map = occupancyMap3D(10)

    Interval for sampling between states and checking state validity, specified as a positive numeric scalar.

    Example: validator.ValidationDistance = 0.1

    Data Types: double

    State variable mapping for xyz-coordinates in the state vector, specified as a three-element vector of form [xIdx yIdx zIdx].

    Data Types: double

    Object Functions

    copyCreate deep copy of state validator object
    isMotionValidCheck if path between states is valid
    isStateValidCheck if state is valid


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    Create a 3-D occupancy map and associated state validator. Plan, validate, and visualize a path through the occupancy map.

    Load and Assign Map to State Validator

    Load a 3-D occupancy map of a city block into the workspace. Specify a threshold for which cells to consider as obstacle-free.

    mapData = load('dMapCityBlock.mat');
    omap = mapData.omap;
    omap.FreeThreshold = 0.5;

    Inflate the occupancy map to add a buffer zone for safe operation around the obstacles.


    Create an SE(3) state space object with bounds for state variables.

    ss = stateSpaceSE3([-20 220;
        -20 220;
        -10 100;
        inf inf;
        inf inf;
        inf inf;
        inf inf]);

    Create a 3-D occupancy map state validator using the created state space.

    sv = validatorOccupancyMap3D(ss);

    Assign the occupancy map to the state validator object. Specify the sampling distance interval.

    sv.Map = omap;
    sv.ValidationDistance = 0.1;

    Plan and Visualize Path

    Create a path planner with increased maximum connection distance. Reduce the maximum number of iterations.

    planner = plannerRRT(ss,sv);
    planner.MaxConnectionDistance = 50;
    planner.MaxIterations = 1000;

    Create a user-defined evaluation function for determining whether the path reaches the goal. Specify the probability of choosing the goal state during sampling.

    planner.GoalReachedFcn = @(~,x,y)(norm(x(1:3)-y(1:3))<5);
    planner.GoalBias = 0.1;

    Set the start and goal states.

    start = [40 180 25 0.7 0.2 0 0.1];
    goal = [150 33 35 0.3 0 0.1 0.6];

    Plan a path using the specified start, goal, and planner.

    [pthObj,solnInfo] = plan(planner,start,goal);

    Check that the points of the path are valid states.

    isValid = isStateValid(sv,pthObj.States)
    isValid = 7x1 logical array

    Check that the motion between each sequential path state is valid.

    isPathValid = zeros(size(pthObj.States,1)-1,1,'logical');
    for i = 1:size(pthObj.States,1)-1
        [isPathValid(i),~] = isMotionValid(sv,pthObj.States(i,:),...
    isPathValid = 6x1 logical array

    Visualize the results.

    hold on
    scatter3(start(1,1),start(1,2),start(1,3),'g','filled') % draw start state
    scatter3(goal(1,1),goal(1,2),goal(1,3),'r','filled')    % draw goal state
        'r-','LineWidth',2) % draw path

    Extended Capabilities

    C/C++ Code Generation
    Generate C and C++ code using MATLAB® Coder™.

    Version History

    Introduced in R2020b