• documentation
main content

scenario simulation -凯发k8网页登录

author scenes, generate sensor data, test algorithms in simulated environments

simulation using realistic unmanned aerial vehicle (uav) scenarios and sensor models is a crucial part of testing uav algorithms. uav toolbox provides two simulation environments in which to test these algorithms. both environments have their uses, and one environment is not a replacement for the other.

  • in the cuboid simulation environment, vehicles and other platforms in the scenario are represented as simple box shapes, or for lidar applications, as polygon meshes. use this environment to rapidly author scenarios or generate sensor data. test controllers, tracking algorithms, and sensor fusion algorithms in both matlab® and simulink®. to get started authoring a scenario, use the object.

  • in the unreal engine® simulation environment, scenarios are rendered using the unreal engine from epic games®. use this environment to visualize scenarios using more realistic graphics; to generate high-fidelity radar, camera, and lidar sensor data; and to test perception-in-the-loop systems. this environment is available in simulink and runs on windows® only. to learn more, see .

apps

design uav scenarios with terrain, platforms, and sensors

functions

generate uav simulation scenario
sensor for uav scenario
uav platform for sensors in scenario
mesh representation of extended object
mission data for uav flight
path planner for uav space coverage
2d coverage area for coverage planner
decompose concave polygon into convex polygons
generate trajectory for multirotor uav from mission
multirotor uav trajectory
generate trajectory for fixed-wing uav from mission
fixed-wing uav trajectory
waypoint trajectory generator
piecewise-polynomial trajectory generator
gps receiver simulation model
inertial navigation system and gnss/gps simulation model
generate point clouds from meshes
create sample implementation for uav custom sensor interface
custom uav sensor interface
define coordinate frames and relative transformations
graph object representing tree structure
get relative transform between frames
list all frame names and stored timestamps
remove frame transform relative to its parent
show transform tree
update frame transform relative to its parent
interface to the unreal engine project
access additional scenes from the server
delete local maps downloaded from the server
download maps from the server
list of locally available maps
list of maps available for download from the server
copy support package files and plugins to specified folders

blocks

reduced-order model for uav
animate uav flight path using translations and rotations
compute and execute a uav autonomous mission
simulate gps sensor readings with noise
simulate ins sensor
place uav vehicle in 3d visualization
scene configuration for 3d simulation environment
camera sensor model with lens in 3d simulation environment
lidar sensor model in 3d simulation environment
fisheye camera sensor model in 3d simulation environment
ultrasonic sensor model in 3d simulation environment
send video stream to remote hardware
configure and simulate uav scenarios
get transforms from uav scenario platforms
simulate lidar measurements based on meshes in scenario
read platform and sensor motions from uav scenario simulation
update platform motion in uav scenario simulation
visualize uav scenario and lidar point clouds

scenes and vehicle dimensions

us city block unreal engine environment
suburban unreal engine environment
quadrotor vehicle dimensions
fixed wing aircraft dimensions

topics

simulation basics


  • learn how to use unmanned aerial vehicle algorithms in simulink and visualize their performance in a virtual environment using the unreal engine from epic games.

  • when simulating in the unreal engine environment, keep these software requirements, minimum hardware requirements, and limitations in mind.

  • learn about the co-simulation framework between simulink and the unreal engine and how block execution order affects simulation.

  • understand the world and uav coordinate systems when simulating in the unreal engine environment.

simulation with sensors


  • this example shows how to create and simulate a uav mission in an urban environment in matlab® and simulink® using the uavmission and uavscenario objects, as well as openstreetmap® (osm) data from manhattan, new york.

  • create a sensor adaptor for an imusensor from navigation toolbox™ and gather readings for a simulated uav flight scenario.

  • the radar sensor enables a uav to detect other vehicles in the airspace, so that the uav can predict other vehicle motion and make decisions to ensure clearance from other vehicles.

  • decide which camera, or lidar sensors to use during 3d simulation with the unreal engine.

  • visualize sensors in a simulation environment that uses unreal engine® from epic games®.

  • this example shows how to visualize depth and semantic segmentation data captured from a camera sensor in a simulation environment.

  • this example shows how to stream simulated camera, depth, and semantic segmentation label data from an unreal engine® scene to nvidia® jetson hardware using the video send block in simulink®.

scene customization


  • customize unreal engine scenes for uav flight applications.

    • step 1:
    • step 2:
    • step 3:
    • step 4:

  • apply labels to objects in a scene so that you can obtain semantic segmentation data from a camera sensor.

  • create custom vehicle mesh for the simulation 3d uav vehicle block.
网站地图