matlab-create-uav-scenario
Create and simulate UAV scenarios with terrain, buildings, platforms, and sensors using uavScenario
Install / Use
npx skills add matlab/matlab-agentic-toolkit --skill matlab-create-uav-scenarioInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Development & EngineeringSupported Platforms
Tags
Our assessment of matlab-create-uav-scenario
matlab-create-uav-scenario scores 88/100 on our quality scale, 2024th of 4,582 Development & Engineering skills we index (top 45%).
Its SKILL.md is 11 KB long, well organised into 17 sections with 13 code examples: a thorough specification that gives an agent plenty to work with.
With 1,098 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 21 days ago, so matlab-create-uav-scenario is actively maintained.
- No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
- Its trust signals score 88/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
matlab-create-uav-scenario compared with similar skills
All 4 of these similar skills score higher than matlab-create-uav-scenario; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| matlab-create-uav-scenario (this skill)by matlab | 88 | 1.1k | 21d ago | SKILL.md |
| ai-job-searchby MadsLorentzen | 100 | 45.1k | 1d ago | CLAUDE.md |
| claude-howtoby luongnv89 | 100 | 41.8k | 6d ago | CLAUDE.md |
| algorithmic-artby anthropics | 100 | 177.9k | 14d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 14d ago | SKILL.md |
Frequently asked questions
- How do I install matlab-create-uav-scenario?
- Run
npx skills add matlab/matlab-agentic-toolkit --skill matlab-create-uav-scenario. The install tabs above show the steps for each supported agent. - Which AI agents does matlab-create-uav-scenario work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is matlab-create-uav-scenario safe to use?
- It declares no license and scores 88/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is matlab-create-uav-scenario still maintained?
- The repository was last updated 21 days ago, so matlab-create-uav-scenario is actively maintained.
Skill content
View source on GitHubname: matlab-create-uav-scenario description: > Create and simulate UAV scenarios with terrain, buildings, platforms, and sensors using uavScenario. Use when building a UAV simulation, UAV simulator, or UAV scenario in MATLAB. Covers addMesh for terrain/building import, uavPlatform with updateMesh, uavSensor adaptor pattern for GPS/IMU, and the setup/advance simulation loop. Triggers on: uavScenario, UAV simulation, UAV simulator, multirotor simulation, quadrotor scenario, terrain import, building import, GPS sensor simulation. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: author: MathWorks version: "1.0"
Create UAV Scenario
Build and simulate UAV scenarios with terrain, buildings, sensor-equipped platforms, and 3D visualization using the UAV Toolbox uavScenario framework.
When to Use
- Creating a UAV simulation environment with real-world terrain or buildings
- Adding sensor-equipped UAV platforms (GPS, IMU, lidar) to a scenario
- Running a time-stepping simulation loop with sensor readings
- Visualizing UAV flight in 3D with
show3D
When NOT to Use
- Generating flight trajectories (waypoint design, min-snap) — use trajectory skill instead
- Simulink-based UAV simulation (UAV Toolbox Simulink blocks)
- Path planning and obstacle avoidance algorithms
- Coordinate conversion only (
ned2lla,lla2ned) — use these directly
Workflow
- Create scenario —
uavScenariowithReferenceLocationandUpdateRate - Add terrain —
addMesh(scene,"terrain",...)with GMTED2010 or custom DTED - Add buildings —
addMesh(scene,"buildings",...)from OSM file - Add platform —
uavPlatformwith trajectory, thenupdateMesh - Attach sensors —
uavSensoradaptor binding sensor to platform - Run simulation —
setup→advance→updateSensors→readloop - Visualize —
show3DwithFastUpdatefor animation
Key Functions
| Function | Purpose | Toolbox |
|----------|---------|---------|
| uavScenario | Create simulation scenario | UAV Toolbox |
| addMesh | Add terrain, buildings, or custom meshes | UAV Toolbox |
| uavPlatform | Add UAV platform to scenario | UAV Toolbox |
| updateMesh | Set platform body mesh | UAV Toolbox |
| uavSensor | Attach sensor to platform | UAV Toolbox |
| setup | Initialize scenario for simulation | UAV Toolbox |
| advance | Step simulation forward one time step | UAV Toolbox |
| updateSensors | Update all sensors at current time | UAV Toolbox |
| show3D | 3D visualization | UAV Toolbox |
| waypointTrajectory | Define flight path from waypoints | Navigation Toolbox |
| gpsSensor | GPS noise model | Navigation Toolbox |
| insSensor | INS/IMU noise model | Navigation Toolbox |
Patterns
Create Scenario with Reference Location
scene = uavScenario( ...
"UpdateRate", 10, ...
"StopTime", 60, ...
"ReferenceLocation", [42.355 -71.066 0]);
ReferenceLocation is [lat lon alt] in degrees and meters. All local coordinates are relative to this origin. Set this before adding any meshes or platforms.
Add Terrain (GMTED2010)
Use geographic coordinates with UseLatLon=true:
latLim = [42.350 42.360];
lonLim = [-71.072 -71.060];
addMesh(scene, "terrain", {"gmted2010", latLim, lonLim}, [0.3 0.6 0.2], ...
UseLatLon=true);
Or use local ENU coordinates (meters) without UseLatLon:
xLim = [-500 500];
yLim = [-500 500];
addMesh(scene, "terrain", {"gmted2010", xLim, yLim}, [0.3 0.6 0.2]);
The geometry cell for terrain is 3 elements: {"gmted2010", xOrLatLim, yOrLonLim}.
The color argument is required — it is not optional.
If user used addCustomTerrain to import DTED file with a terrain name, this terrain can be used in addition to gmted2010.
addCustomTerrain("myterrain", "myterrain.dt1");
xLim = [-500 500];
yLim = [-500 500];
addMesh(scene, "terrain", {"myterrain", xLim, yLim}, [0.3 0.6 0.2]);
Add Buildings (OSM File)
osmFile = "boston_common.osm";
latLim = [42.350 42.360];
lonLim = [-71.072 -71.060];
addMesh(scene, "buildings", {osmFile, latLim, lonLim, 'auto'}, ...
[0.6 0.6 0.6], UseLatLon=true);
Or use local ENU coordinates (meters) without UseLatLon:
xLim = [-500 500];
yLim = [-500 500];
addMesh(scene, "buildings", {osmFile, xLim, yLim, 'auto'}, [0.3 0.6 0.2]);
The geometry cell for buildings is 4 elements: {osmFile, latOrXLim, lonOrYLim, height}. height can either be 'auto' or a numerical scalar. Auto will snap buildings to terrain height if available.
The color argument is required — it is not optional.
Add Platform with Mesh
traj = waypointTrajectory( ...
"Waypoints", [0 0 -50; 200 0 -50; 200 200 -50; 0 0 -50], ...
"TimeOfArrival", [0 20 40 60], ...
"ReferenceFrame", "NED");
plat = uavPlatform("UAV1", scene, "Trajectory", traj);
updateMesh(plat, "quadrotor", {1}, [0 0.4 0.8], [0 0 0], [0 1 0 0]);
updateMesh requires all arguments: (platform, type, geometries, color, position, orientation).
geometries— 1-element cell:{scaleFactor}for"quadrotor"/"fixedwing",{[L W H]}for"cuboid"color— RGB triplet (required, not optional)position—[x y z]offset, use[0 0 0]for defaultorientation— quaternion[w x y z], use[0 1 0 0]for NED scenarios (180-degree roll to flip z-down body frame upright)
Valid mesh types: "fixedwing", "quadrotor", "cuboid", "custom".
There is NO "multirotor" type — use "quadrotor" for any multirotor UAV.
Attach Sensors (uavSensor Adaptor Pattern)
Always use uavSensor to bind sensors to platforms. Do not feed sensor models manually.
% Create sensor model
gps = gpsSensor("SampleRate", 10, "ReferenceFrame", "NED");
% Bind to platform via uavSensor adaptor
gpsSensorObj = uavSensor("GPS", plat, gps, "UpdateRate", 10);
For INS:
ins = insSensor;
insSensorObj = uavSensor("INS", plat, ins, "UpdateRate", 10);
Sensor UpdateRate must divide evenly into the scenario UpdateRate. For example, a 10 Hz scenario supports sensor rates of 1, 2, 5, or 10 Hz — not 100 Hz.
Simulation Loop
setup(scene);
while advance(scene)
updateSensors(scene);
% Read sensor data (3 outputs: isUpdated, timestamp, readings)
[isUpdated, t, position, velocity, groundspeed, course] = read(gpsSensorObj);
if isUpdated
% position is 1x3 [lat lon alt] for gpsSensor
gpsLLA = position;
end
% Read platform state directly
[motion, lla] = read(plat);
% motion: 1x16 vector [pos(3) orient(4) vel(3) acc(3) angvel(3)]
% lla: [lat lon alt]
end
read(sensor) returns variable number outputs:
isUpdated— logical, true when sensor has new data at this time stept— timestamp in secondssensorReadings1tosensorReadingsN— sensor-specific output (position, velocity, groundspeed, courseforgpsSensor)
read(plat) returns exactly 2 outputs:
motion— 16-element vector: position(1:3), orientation quaternion(4:7), velocity(8:10), acceleration(11:13), angular velocity(14:16)lla— 3-element vector: [latitude, longitude, altitude]
Visualize with show3D
setup(scene);
ax = show3D(scene);
while advance(scene)
updateSensors(scene);
show3D(scene, "FastUpdate", true, "Parent", ax);
drawnow limitrate
end
Use "FastUpdate", true after the first call for efficient animation.
Trajectory Trail (Flight Path Line)
show3D only renders the UAV at its current position — it does NOT draw the flight path. To show the trajectory trail, create a line object once, then update its data each step:
setup(scene);
[ax, plottedFrames] = show3D(scene);
hold(ax, "on");
% Draw trajectory in the platform's reference frame
trajLine = plot3(plottedFrames.(plat.ReferenceFrame), NaN, NaN, NaN, "r-", "LineWidth", 1.5);
hold(ax, "off");
% acceptable for short loops; pre-allocate for long simulations
xHist = []; yHist = []; zHist = [];
while advance(scene)
show3D(scene, "FastUpdate", true, "Parent", ax);
[motion, ~] = read(plat);
xHist(end+1) = motion(1);
yHist(end+1) = motion(2);
zHist(end+1) = motion(3);
set(trajLine, "XData", xHist, "YData", yHist, "ZData", zHist);
drawnow limitrate
end
Do NOT call plot3 inside the loop — it creates a new graphics object each step and kills performance.
Body-Frame Marker (Visibility in Large Scenes)
When scenes span 500m+, the platform mesh becomes invisible regardless of scale factor. Instead of inflating the scale (which distorts the mesh), parent a marker to the platform's body frame so it tracks at any zoom level:
setup(scene);
[ax, plottedFrames] = show3D(scene);
hold(ax, "on");
bodyFrame = plottedFrames.UAV1.BodyFrame;
plot3(ax, 0, 0, 0, "r^", "MarkerSize", 15, "MarkerFaceColor", "r", ...
"Parent", bodyFrame);
hold(ax, "off");
while advance(scene)
show3D(scene, "FastUpdate", true, "Parent", ax);
drawnow limitrate
end
Replace UAV1 with the actual platform name. The marker moves with the UAV automatically via the parent transform.
Gotchas
| Mistake | Consequence | Fix |
|---------|-------------|-----|
| addMesh(...,latLim,lonLim) without UseLatLon=true | 0 buildings imported, terrain at wrong location | Add UseLatLon=true when passing geographic coordinates |
| updateMesh(plat,"multirotor",...) | Error — invalid mesh type | Use "quadrotor" |
| updateMesh with [1 0 0 0] (identity quaternion) in NED scenario | Inverted or invisible mesh — body frame is z-down | Use [0 1 0 0] (180-degree roll) to flip mesh upright |
| [pos, orient, vel] = read(plat) | Error — too many outputs | Use [motion, lla] = read(plat) (2 outputs) |
| [isUpdated, data] = read(sensor) | Gets timestamp instead of readings | Use [isUpdated, t, sensorReadings] = read(sensor) (3 outputs) |
| Feeding gpsSensor manually each step | Works but bypasses the scenario framework | Use uavSensor adaptor + updateSensors(scene) |
| Missing color argument in addMesh | Error — not enough input arguments | Always provide RGB triplet as 4th argument |
| waypointTrajectory in ENU with NED platform | Error — reference frame mismatch | Set "ReferenceFrame","NED" on trajectory |
| Forgetting setup(scene) before loop | Sensors not initialized, no readings | Always call setup(scene) before advance |
| Sensor UpdateRate > scenario UpdateRate | Error — rate must divide evenly | Sensor rate must be ≤ scenario rate and divide evenly into it |
Conventions
- NED frame is the default for
uavPlatform. Match all trajectories and sensors to NED. ReferenceLocationmust be set at scenario creation — it is read-only after construction.UpdateRateon the scenario controls the simulation time step. SensorUpdateRatecan differ (sensors skip steps when not due).- OSM files must be downloaded separately (e.g., via Overpass API or export from openstreetmap.org).
addMesh("buildings",...)expects a file path, not a URL. addCustomTerrainfor DTED files when GMTED2010 resolution is insufficient.
Copyright 2026 The MathWorks, Inc.
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