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Roboclaws

CI (main) Live Reports Python Install License

Let's Bring Brain To Robots

Visible robotics demos driven by VLM policies, OpenClaw, and AI coding agents.

Roboclaws is a thin demo repo for making AI-driven robotics behavior reviewable: frames, maps, tool traces, scores, and public/private evaluation boundaries are published as HTML reports instead of buried in terminal logs.

Skill-first robotics

It answers three practical questions:

  • How can an AI agent drive a robot?
  • What context and tools does the agent need?
  • What did the agent actually do in the simulated or robot-backed world?

MCP and Skill Design Principles

Roboclaws treats reusable robot behavior as skills first and MCP tools as a bounded public robot capability surface.

Principle Practice
Start from open-ended goals A user asks for work such as "clean the room" or "take useful photos"; an agent selects or creates a skill to do it.
Keep strategy in skills Skills own prompt strategy, scripts, examples, checks, and task-specific loops such as photo capture or cleanup.
Keep MCP bounded MCP tools expose semantic robot capabilities like observe, move, pick, place, and done; they should not hide a whole task behind one opaque call.
Profile public capabilities Semantic profiles describe the public tool contract for a backend/domain, currently ai2thor_navigation_v1 and molmospaces_cleanup_v1.
Label privileged help Simulator or demo helpers such as full object inventory and target-relative teleport are useful, but they stay labeled as privileged tools, not canonical robot abilities.
Protect private evaluation truth Hidden mess sets, acceptable destinations, private manifests, and scoring truth stay out of public profile metadata and agent-facing skill inputs.
Let reports improve skills Traces, artifacts, and evals feed the skill lifecycle: improve, split, merge, prune, or promote behavior only when the boundary is stable.

The working abstraction ladder is:

open-ended goal
  -> agent skill
  -> composite action
  -> semantic capability
  -> environment primitive
  -> execution backend

Default decision: improve or add a skill. Promote behavior into MCP only when multiple skills need it, the input/output shape is stable, public/private boundaries are clear, and traces can preserve the important substeps. The detailed profile and skill reference is docs/human/mcp-skills-and-semantic-profiles.md.

Run Demos With Just

Install the project once:

uv sync --extra dev --extra openclaw

For MolmoSpaces/MuJoCo cleanup demos, include the heavier extra:

uv sync --extra dev --extra molmospaces

The public command grammar is:

just task::run <task> <driver> [report|profile] [key=value ...]

For full command routing, profiles, and maintainer-only recipes, read just/README.md.

Demo Matrix

GitHub Actions publishes the report site at miaodx.com/roboclaws. If a link looks stale, check the CI workflow: Pages republishes from successful main runs.

Demo What it proves Run it locally Live CI report
AI2-THOR territory Multiple robots compete for reachable cells in an iTHOR scene. Local VLM route is being repaired; use mock/OpenClaw reports for now. mock, Kimi smoke, OpenClaw
AI2-THOR coverage Multiple robots cooperate to cover as much of the room as possible. just task::run coverage vlm visual agents=2 steps=100 mock, Kimi smoke, OpenClaw
OpenClaw navigation OpenClaw Gateway agents control robots through the shared Roboclaws APIs. just task::run ai2thor-nav openclaw visual openclaw/demo/report.html
Coding-agent MCP control Docker-backed Codex or Claude Code drives the robot directly through MCP tools. just task::run ai2thor-nav codex visual or just task::run ai2thor-nav claude visual Local-only today; reports write to output/runs/<stamp>/.
Photo task A robot navigates the room and photographs chairs/sofas. just task::run photo-chairs openclaw visual Local/OpenClaw report artifact.
MolmoSpaces cleanup A cleanup agent tidies a generated household mess while private scoring stays hidden. just task::run molmo-cleanup direct world-labels seed=7 generated_mess_count=5 Molmo live index, Kimi K2.6, MiMo v2.5 Pro, MiMo v2 Omni
MolmoSpaces live agent Docker-backed Claude Code or Codex connects to the cleanup MCP server and produces the same cleanup report shape. just task::run molmo-cleanup claude world-labels seed=7 generated_mess_count=5 Same Molmo live index; CI currently runs Claude Code through Kimi/MiMo provider profiles.
Railway appliance Single-container hosted demo with UI, viewer, Gateway, and AI2-THOR. DEMO_PASSWORD=demo just appliance::run local Local appliance surface.
Maintainer gate Fast mock confidence check before shipping repo changes. just agent::verify mock CI status: workflow

See ARCHITECTURE.md for the code map and the full operating mode contract.

Documentation Map

Need Read
Code map and operating modes ARCHITECTURE.md
Human setup/runbooks/domain docs docs/human/README.md
Detailed MCP profile reference docs/human/mcp-skills-and-semantic-profiles.md
Skill library convention skills/README.md
Public command grammar just/README.md
Local keys and report artifacts docs/human/local-runtime.md
Coding-agent navigation guide docs/human/coding-agent-nav-server.md
MolmoSpaces settings docs/human/molmospaces-settings.md
Current project focus STATUS.md
Agent operating rules AGENTS.md

Related Projects

  • Roboharness - visual testing harness for AI coding agents in robot simulation
  • Robowbc - whole-body-control experiments
  • OpenClaw - open-source personal AI assistant
  • ROSClaw - OpenClaw to ROS 2 bridge
  • AI2-THOR - interactive 3D indoor simulation

License

MIT

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Visible AI-driven robotics demos powered by VLM policies, MCP skills, and AI coding agents. Reviewable HTML reports — frames, maps, tool traces, scores — instead of buried terminal logs.

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