122 个（carla-simulator 的仓库） · 按人气排序
Checks a local CARLA checkout for missing API documentation, outdated references, broken links, and pages absent from navigation. Produces a grouped Markdown report without building the project or running the simulator.
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Fill documentation gaps identified by a CARLA documentation audit, following the project's writing style. Work through one category at a time, assess which findings deserve entries, update source files, and report changes and skipped findings.
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Start a CARLA simulator server from a downloaded release, packaged build, or source checkout. It selects the launch mode, supports headless or windowed operation, checks client connectivity, and guides clean shutdown.
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Package a CARLA server built with UE 5.8 for distribution, choosing which maps to include. Inspect the resulting files for mismatched containers, missing road data, and exposure settings that can cause runtime failures.
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Start, inspect, and stop a CARLA UE 5.8 server. Choose an editor-based server, packaged build, or full editor; configure headless operation and ports; and enable native ROS 2 integration when the build supports it.
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Check which CARLA features are missing on UE 5.5 compared with UE 5.8. Read source markers to identify the checkout, review unsupported workflows, and see which UE 5.8 procedures also apply.
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Prepare and launch Autoware with CARLA on UE 5.8 through its native ROS 2 interface. Check communication topics and sensors, generate required maps, and configure either the classical stack or camera-only VAD model.
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Import a custom pedestrian into CARLA on UE 5.8, connect it to the shared animation skeleton, and verify that it moves. Export an existing walker as an FBX starting point or investigate a walker that stands still.
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Import FBX 3D models into CARLA on UE 5.8 and register them as props that can be placed in a simulation. Check measured dimensions, adjust scale, verify placement on a running server, and undo imports when needed.
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Create, migrate, refine, or debug CARLA vehicle assets with Blender and Unreal. Use real vehicle references to guide geometry and materials, configure wheels, lights, and physics, and deliver editable sources with evidence from runtime validation.
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Guides custom map imports into CARLA on UE 5.8, from FBX geometry and OpenDRIVE road data to packaging or temporary road generation. Helps choose a supported route and verify map files and loading.
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Build CARLA for Unreal Engine 5.8 using CMake, the tool that configures its build process. The skill guides engine setup, optional ROS 2 support, Python API rebuilding, editor builds, and checks that the expected files were actually produced.
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Populate a running CARLA simulation with autonomous traffic, evenly spaced vehicles in one lane, or a single vehicle for control and sensors. Filter vehicle models, keep automated driving active, and remove vehicles when the scene is finished.
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Record a running CARLA simulation to a .log file for later replay or inspection. Capture object creation, movement, and traffic-light states, optionally include controls and velocities, and verify that the recording contains simulation frames.
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Control CARLA’s on-screen camera to view a vehicle from behind, above, the driver’s seat, or the front. Select vehicles by name, role, or ID, frame them once, or follow them as they move.
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Control street, building, and vehicle light sources in CARLA. Switch groups on or off, adjust their color and brightness, and enable automatic nighttime lighting to prepare illuminated city scenes or blackouts.
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Extend CARLA’s native ROS 2 interface to publish sensor data or receive vehicle commands. Covers topic implementation, registration, data connections, and verification, plus adding middleware, the communication layer used to exchange messages.
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Replay a recorded CARLA simulation in full or over a selected time range. Change playback speed, follow a particular vehicle, restore recorded weather, or regenerate sensor data to examine the run again.
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Read and display CARLA object bounding boxes, then project them onto a camera image as 2D rectangles. Export an annotated PNG and box coordinates in JSON for object detection annotation work.
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Install Scenic, a language for describing scenarios with randomized conditions, into the Python environment used by CARLA. Check command-line tools and version compatibility, optionally download example scenarios and map assets, and save the installation paths.
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Set up a CARLA driving evaluation environment for Leaderboard 1.0, 2.0, or 2.1. Match the simulator and scenario_runner versions, configure Python paths, and verify that the required components load correctly.
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Read CARLA Leaderboard result files to understand driving scores, route completion, and penalties. Investigate low scores, compare two runs, merge split results, or recalculate scores under version 2.0 or 2.1 rules without rerunning the simulation.
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List static objects built into a CARLA map and hide or restore them by category or asset name. Adjust buildings, vegetation, fences, and other scenery, preview affected objects, and change both their visibility and collision behavior.
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Turn a written traffic situation into a Scenic file, which describes possible scenes using placement rules and constraints. Select suitable maps and actors, then check that the file compiles and can generate at least one scene.
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