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world-data

Queries the live CARLA world and resolves an entity description into a concrete actor id — find actors by type, role, or colour, or the single one nearest a point/actor; read the world snapshot; get static level bounding boxes by label; cast rays for semantic points; project a point to the ground; or (ros-topics) list the native ROS 2 topics each actor should be publishing and why any is silent. Identifies by stable attributes, not by any rank/order. Use when the user asks "what actors are here", "find the red prius", "the vehicle nearest the ego", "list the pedestrians", or needs a specific actor id for another skill.

インストール方法を見る

含まれるファイル(5)

  • SKILL.md8.2 KB
  • references/world-data.md2.8 KB
  • scripts/check_env.sh2.1 KB
  • scripts/env.sh1.1 KB
  • scripts/world_data.py14.4 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Query the world (and resolve entities)

Paths. scripts/… and references/… below are relative to the directory holding this SKILL.md. Your working directory is the user's project, not that directory, so prefix them with its absolute path or the command is not found.

The resolver skill. Other skills act on one entity by id; this one finds that id when the request is a description — "a prius" (but there are three), "the nearest walker", "the 3rd vehicle". It also reads world-level data: snapshot, level bounding boxes, raycasts, ground projection.

Identifying a specific actor (the core use)

There is no ordering / rank — peer actors have no meaningful order, so "the 3rd one" is not a thing. Identify by a stable attribute or a spatial predicate, narrowing until one remains, then use its id:

  • by type/blueprint: --filter '*prius*', --filter walker.pedestrian.*
  • by role: --role hero
  • by colour (tells identical models apart): --color 255,0,0
  • the single closest to a point/actor: --near X,Y,Z / --near-id N with --nearest (a predicate — "the closest" — not an index)
  • --full dumps every attribute (colour, role, size, yaw), so you can spot the distinguishing field and filter by it (or just read the id)

So "the red prius" → actors --filter '*prius*' --color 255,0,0; "the prius nearest the ego" → actors --filter '*prius*' --near-id <ego> --nearest. Either yields an id to hand to telemetry / bounding-boxes / control-vehicle / control-spectator. For junctions ("3-way intersections") use the map-waypoints skill's junctions --arms 3.

Moving objects: a distance is a single-frame snapshot and changes as actors move, so --nearest is only "closest right now". The id is the stable handle — resolve once, then act on the id; re-query for a fresh distance. (An inherent order only exists in special cases like a queue of vehicles along a lane — that is a lane query, not this generic actor list.)

Instructions

Progress:
- [ ] Step 1: Check prerequisites (bash scripts/check_env.sh), clear FAILs
- [ ] Step 2: actors --filter/--role/--color [--nearest] until one remains → its id
- [ ] Step 3: hand the id to the action skill; or use snapshot/level-bbox/raycast/ground

Commands need CARLA_HOST/CARLA_PORT from scripts/env.sh. Negative coordinates: use the = form (--near=-24,-57,0.6).

Step 1: Check prerequisites

bash scripts/check_env.sh

Step 2-3: Query

source scripts/env.sh

python3 scripts/world_data.py actors                              # everything (non-traffic)
python3 scripts/world_data.py actors --filter '*prius*'           # all priuses (ids + locations)
python3 scripts/world_data.py actors --filter '*prius*' --full    # + color/role/size to tell them apart
python3 scripts/world_data.py actors --filter '*prius*' --color 255,0,0          # the red one
python3 scripts/world_data.py actors --filter '*prius*' --near-id 100 --nearest  # closest to actor 100
python3 scripts/world_data.py snapshot                            # frame / time / count
python3 scripts/world_data.py level-bbox --label TrafficSigns     # static boxes by label
python3 scripts/world_data.py raycast --from=0,0,1 --to=50,0,1    # semantic hits along a ray
python3 scripts/world_data.py ground --at=20,20,50               # drop to the ground
python3 scripts/world_data.py ros-topics                          # ROS 2 topic tree per actor

Resolving ROS 2 topics (ros-topics)

The same resolver job, one level up: it maps live actors to the topics the server should be publishing, and names the reason for each silent one. It needs no ROS 2 installation — it derives the names the way the server does, so it answers the half ros2 topic list cannot ("the topic is missing — why?").

world topics (exist whenever the server runs with --ros2):
  rt/clock       [rosgraph_msgs/Clock]  every tick
  rt/carla/map   [std_msgs/String]      OpenDRIVE, LATCHED, re-sent on map load
  rt/tf          [tf2_msgs/TFMessage]   per registered actor, unless ros_publish_tf=false

hero vehicle(s): 1
  id=112 vehicle.lincoln.mkz_2017 ros_name=hero
    <- rt/carla/hero/vehicle_control_cmd     [carla_msgs/CarlaEgoVehicleControl]
    <- rt/carla/hero/ackermann_control_cmd   [ackermann_msgs/AckermannDriveStamped]

sensors: 2
  id=113 sensor.camera.rgb ros_name=front  [NOT enabled_for_ros -> SILENT]
    -> rt/carla/hero/front/image        [sensor_msgs/Image]
    -> rt/carla/hero/front/camera_info  [sensor_msgs/CameraInfo]
  id=114 sensor.other.obstacle ros_name=actor114
    (no native publisher for sensor.other.obstacle)

Three reasons an expected topic is absent, all visible above: the sensor is not enable_for_ros()-ed ([[create-sensor]] ros --id N), the sensor type has no publisher at all, or the vehicle is not role_name = hero (only the hero is registered). If even rt/clock is missing, the problem is upstream — the build or the launch flag ([[run-carla-server]] ROS2=1).

On CARLA 0.10.0 (the UE5 line: 5.5 and 5.8)

ros-topics is the only mode that changes. rt/carla/map does not exist on 0.10.0: CarlaMapPublisher is present in 0.9.x and absent from LibCarla/source/carla/ros2/publishers/ in 0.10.0, so nothing ever advertises the OpenDRIVE topic. The mode detects the server version and says so rather than listing a topic you would then hunt for; read the map with map.to_opendrive() over RPC instead.

rt/clock and rt/tf behave the same on both. On 0.10.0, rt/tf publishing is additionally gated globally by World.set_publish_tf(), which is new.

The actor-query modes are unchanged, and 0.10.0 adds a few worth knowing: world.get_traffic_sign(), world.get_names_of_all_objects() and world.set_imu_sensor_gravity() — plus world.get_ego_spawn_points() and world.spawn_custom_mesh(), which are UE 5.8 only ([[check-ue5-limitations]]). CityObjectLabel gained Rock, which matters for level-bbox if you hard-code label integers.

Examples

Example 1: 1 vehicle among many

User says: "get the prius closest to me" (ego = id 100)

actors --filter '*prius*' --near-id 100 --nearest → e.g. id=137. Then telemetry show --id 137. (Or "the red prius" → --color 255,0,0.)

Example 2: survey the scene

User says: "what's around?"

actors for the movable actors, snapshot for the frame/count.

Example 3: where's the ground here

User says: "what's the ground height at (20, 20)?"

ground --at=20,20,50 → projects down to the road surface + its semantic label.

Troubleshooting

Problem: too many actors match Cause: broad filter. Solution: narrow by --role/--color, or take --nearest --near-id N; use --full to find a distinguishing attribute, then the id.

Problem: expected actor not listed Cause: it's a traffic light/sign/spectator (hidden by default). Solution: add --all.

Problem: raycast/ground returns nothing Cause: the ray misses geometry, or no ground within --search. Solution: widen the ray / raise --search; check the start point is above ground.

Outputs

Text listings (actors, boxes, points) — no world change. The actor ids it prints are inputs for the action skills.

Detail (attribute/nearest selection, level bbox labels, cast_ray/project_point, snapshot fields) in references/world-data.md.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Adds a new ROS 2 message type to CARLA's native ROS 2 interface — the hand-written POD struct under LibCarla/source/carla/ros2/types/msg, its Fast-CDR serialize/deserialize pair, the RIHS01 type hash computed in Docker, the CdrTopicInfo registration and the type-hash test. Use when the user asks to "add a ROS message type", "support sensor_msgs/X in CARLA", "add a carla_msgs type", "why is my type hash warning appearing", or needs a message CARLA does not publish yet. There is no IDL codegen — every step is manual.

日本語の概要は準備中です。原文の説明を表示しています。

carla-simulator/carla-agentic-tools42026年9月12日 更新

Adds a new topic to CARLA's native ROS 2 interface — a publisher (BasePublisher + PublisherImpl, topic suffix, QoS, registration in ROS2::GetOrCreateSensor, a ProcessDataFrom* entry point and its call site in the UE4 plugin) or a subscriber that lets ROS drive an actor. Also covers adding a middleware (RMW) behind IPublisherMiddleware. Use when the user asks to "publish X to ROS from CARLA", "add a ROS topic/publisher/subscriber", "make the obstacle/lane-invasion sensor publish", "add odometry to ROS", or "add another RMW".

日本語の概要は準備中です。原文の説明を表示しています。

carla-simulator/carla-agentic-tools42026年9月12日 更新

Reads and summarises ScenarioRunner output — the criteria pass/fail tables from --output/--file, the machine-readable --json and --junit result files, and the criteria JSON written alongside a --record recording — and runs the metrics module (metrics_manager.py) to compute custom measurements over a recorded run offline, without the simulator. Use when the user asks "did the scenario pass", "why did it fail", "summarise these results", "compare these runs", or wants distance/speed/lane metrics from a recording.

日本語の概要は準備中です。原文の説明を表示しています。

carla-simulator/carla-agentic-tools42026年9月12日 更新

Gets actor and level 3D bounding boxes and projects them into a camera image as 2D boxes — the dataset-annotation workflow. Lists box geometry, draws 3D boxes in the world via debug, or captures one camera frame and writes an annotated PNG plus a JSON of 2D boxes for matching actors. Use when the user asks to "get bounding boxes", "draw boxes around the cars", "project boxes onto the camera", or "generate a detection dataset / annotations".

日本語の概要は準備中です。原文の説明を表示しています。

carla-simulator/carla-agentic-tools42026年9月12日 更新

Builds CARLA (branch ue4-dev, Unreal Engine 4.26) from source on Linux end-to-end — UE4 fork, the Carla server (editor C++ modules), the LibCarla Python client wheel, and content — then verifies them against a from-source server. Optionally builds the native ROS 2 interface in (ROS2=1 → --ros2, Fast-DDS/CycloneDDS/Zenoh), which is compile-time only and cannot be enabled later. Use when the user asks to "build CARLA from source", "compile CARLA ue4-dev", "set up CARLA on Ubuntu (incl. 24.04)", "build CARLA with ROS2 support", or "produce a CARLA server + client wheel". Cooking a distributable Dist/ package is a separate skill (package-carla-ue4); running the build is run-carla-server.

日本語の概要は準備中です。原文の説明を表示しています。

carla-simulator/carla-agentic-tools42026年9月12日 更新

Builds CARLA on Unreal Engine 5.8 from the ue58-dev branch using its CMake build system — configure a preset, then build the carla-unreal / carla-unreal-editor / carla-python-api-install / launch targets — with ROS 2, DLSS, RSS and cook-scope options, and the engine-side build of the CarlaUnreal UE 5.8 fork. There is no Makefile and no Util/BuildTools in this tree, so every UE4 `make` recipe is invalid here. Use when the user asks to "build CARLA UE5", "build ue58-dev", "compile CARLA with cmake", "rebuild the Python API", or hits a CMake configure or target failure.

日本語の概要は準備中です。原文の説明を表示しています。

carla-simulator/carla-agentic-tools42026年9月12日 更新

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