GitHub collection
robium-ai/robium
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44 skills imported from this repository.
app-publishing
Post-build editorial publication for an already implemented and smoke-tested robium reference application: compose its catalog entry, overview, working surface, article/guide, source links, media, and metadata from repository-owned facts. Use when: 'publish this finished applicat
architect
Entry-point skill for designing robotics applications with AI agents. Turns requirements (robot type, task, hardware, sim-vs-real, GPU/budget) into a full stack decision — middleware, simulation, data, visualization, training frameworks — plus a scaffold plan and a written archit
architect
Entry-point skill for designing robotics applications with AI agents. Turns requirements (robot type, task, hardware, sim-vs-real, GPU/budget) into a full stack decision — middleware, simulation, data, visualization, training frameworks — plus a scaffold plan and a written archit
architect
Entry-point skill for designing robotics applications with AI agents. Turns requirements (robot type, task, hardware, sim-vs-real, GPU/budget) into a full stack decision — middleware, simulation, data, visualization, training frameworks — plus a scaffold plan and a written archit
architect
Entry-point skill for designing robotics applications with AI agents. Turns requirements (robot type, task, hardware, sim-vs-real, GPU/budget) into a full stack decision — middleware, simulation, data, visualization, training frameworks — plus a scaffold plan and a written archit
architect
Entry-point skill for designing robotics applications with AI agents. Turns requirements (robot type, task, hardware, sim-vs-real, GPU/budget) into a full stack decision — middleware, simulation, data, visualization, training frameworks — plus a scaffold plan and a written archit
architect
Entry-point skill for designing robotics applications with AI agents. Turns requirements (robot type, task, hardware, sim-vs-real, GPU/budget) into a full stack decision — middleware, simulation, data, visualization, training frameworks — plus a scaffold plan and a written archit
architect
Entry-point skill for designing robotics applications with AI agents. Turns requirements (robot type, task, hardware, sim-vs-real, GPU/budget) into a full stack decision — middleware, simulation, data, visualization, training frameworks — plus a scaffold plan and a written archit
architect
Entry-point skill for designing robotics applications with AI agents. Turns requirements (robot type, task, hardware, sim-vs-real, GPU/budget) into a full stack decision — middleware, simulation, data, visualization, training frameworks — plus a scaffold plan and a written archit
architect
Entry-point skill for designing robotics applications with AI agents. Turns requirements (robot type, task, hardware, sim-vs-real, GPU/budget) into a full stack decision — middleware, simulation, data, visualization, training frameworks — plus a scaffold plan and a written archit
architect
Entry-point skill for designing robotics applications with AI agents. Turns requirements (robot type, task, hardware, sim-vs-real, GPU/budget) into a full stack decision — middleware, simulation, data, visualization, training frameworks — plus a scaffold plan and a written archit
architect
Entry-point skill for designing robotics applications with AI agents. Turns requirements (robot type, task, hardware, sim-vs-real, GPU/budget) into a full stack decision (middleware, simulation, data, visualization, training frameworks) plus a scaffold plan and a written architec
architect
Entry-point skill for designing robotics applications with AI agents. Turns requirements (robot type, task, hardware, sim-vs-real, GPU/budget) into a full stack decision (middleware, simulation, data, visualization, training frameworks) plus a scaffold plan and a written architec
architect
Entry-point skill for shaping new robotics applications: lightweight brainstorming, project ideation, requirement/risk discovery, stack selection, comparing or choosing simulators/models/visualization, a first user-visible slice, and a concise architecture decision record. Use wh
architect
Entry-point skill for shaping new robotics applications: lightweight brainstorming, project ideation, requirement/risk discovery, stack selection, comparing or choosing simulators/models/visualization, a first user-visible slice, and a concise architecture decision record. Use wh
cloud-run
Deploy headless robotics / sim / demo containers to Google Cloud Run: the build → Artifact Registry → Cloud Run path plus the gotchas that bite sim workloads (no UDP multicast for gz-transport/DDS, CPU allocated only while a request is open, session affinity for per-visitor insta
cloud-run
Deploy headless robotics / sim / demo containers to Google Cloud Run: the build → Artifact Registry → Cloud Run path plus the gotchas that bite sim workloads (no UDP multicast for gz-transport/DDS, CPU allocated only while a request is open, session affinity for per-visitor insta
cloud-run
Deploy headless robotics / sim / demo containers to Google Cloud Run: the build → Artifact Registry → Cloud Run path plus the gotchas that bite sim workloads (no UDP multicast for gz-transport/DDS, CPU allocated only while a request is open, session affinity for per-visitor insta
data
Data sourcing strategy for robotics and physical-AI: choose between offline datasets (HuggingFace hub, Open X-Embodiment and similar), simulation-generated data, and teleop/real-robot collection; plan storage formats, episode structure, and dataset versioning. Use when: 'where do
data
Data sourcing strategy for robotics and physical-AI: choose between offline datasets (HuggingFace hub, Open X-Embodiment and similar), simulation-generated data, and teleop/real-robot collection; plan storage formats, episode structure, and dataset versioning. Use when: 'where do
data
Data sourcing strategy for robotics and physical-AI: choose between offline datasets (HuggingFace hub, Open X-Embodiment and similar), simulation-generated data, and teleop/real-robot collection; plan storage formats, episode structure, and dataset versioning. Use when: 'where do
environments
Set up reproducible robotics environments with uv, Docker, or GPU hosts.
gemini-robotics
Integrate and debug Gemini Robotics ER perception, function calls, and guarded execution. For a first natural-language robot assistant demo, start with architect's reference-app selection.
huggingface
Inspect and manage robotics datasets, models, Jobs, and Spaces on Hugging Face.
integration
Wire robotics modules with ROS 2 interfaces, Docker Compose, or non-ROS transports.
learning-loop
Turn captured Robium experience into small, evidence-backed skill improvements.
navigation
Configure, extend, and debug Nav2 in an existing robot app; explain navigation concepts. New mapping/localization/navigation demos start with architect.
skill-author
Author and structure practical Robium skills without unnecessary context or ceremony.
test-assets
Choose and manage reproducible worlds, models, datasets, and recordings for robotics tests.
visualization
Choose between RViz2, Foxglove, Lichtblick, and Rerun to inspect robot behavior.