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No ROS installation required.\r\n- **SLAM + sensor fusion** — occupancy-grid SLAM (correlative scan matching)\r\n  and an EKF fusing odometry + IMU with online gyro-bias estimation, running\r\n  as babyros nodes — or attached to **your real robot's rosbridge**.\r\n- **HAL** — a versioned WebSocket protocol (e-stop, watchdog, skills,\r\n  telemetry) linking the OS to any robot that runs the bundled\r\n  `zelpi-robot-agent`, with a ROS 1/2 driver included.\r\n- **Real models** — `zelpi hub install` downloads real VLA checkpoints\r\n  (SmolVLA, ACT, Diffusion Policy) from HuggingFace and runs real inference;\r\n  `zelpi gpu setup` switches the venv to CUDA.\r\n- **Honest MuJoCo simulations** — a humanoid driven by a learned 40-DoF\r\n  action model (`zelpi sim`), and a Shadow Dexterous Hand doing\r\n  language-commanded pick-and-place (`zelpi demo2`).\r\n\r\n## Five minutes to a live SLAM map\r\n\r\n```bash\r\nnpx zelpi slam launch        # simulated robot + lidar → EKF + SLAM → live ASCII map\r\n```\r\n\r\nThat boots a babyros broker, a 2D differential-drive world with a 180-beam\r\nlidar (3% odometry slip, gyro bias — deliberately imperfect), an EKF fusion\r\nnode, and an occupancy-grid SLAM node, then renders the map live in your\r\nterminal. On a reference run the fused estimate tracked the true pose at\r\n**0.05 m error vs 0.14 m from raw odometry**, with the gyro bias estimated to\r\nwithin 3%.\r\n\r\nHave a real robot publishing `sensor_msgs/LaserScan` + odometry on a\r\nrosbridge? Attach the same nodes to it:\r\n\r\n```bash\r\nnpx zelpi slam attach --url ws://<robot>:9090 --scan /scan --odom /odom --imu /imu\r\n```\r\n\r\nMore first commands:\r\n\r\n```bash\r\nnpx zelpi babyros up                        # standalone middleware (port 9091)\r\nnpx zelpi babyros topics                    # zelros + roslibjs connect unchanged\r\nnpx zelpi hal connect ws://<robot>:9091     # native robot link (e-stop, skills, telemetry)\r\nnpx zelpi hub install smolvla               # real HuggingFace weights + local inference\r\nnpx zelpi gpu setup                         # CUDA torch for the models venv\r\nnpx zelpi docs hardware                     # the full real-hardware integration guide\r\n```\r\n\r\n## Demo mode — the fleet-OS software twin\r\n\r\nZelPi also ships a **complete simulated fleet OS**: a cross-timescale neural\r\nstack (System 2 planning / System 1 skills / System 0 reflexes), an agent\r\nswarm, a Safety Broker with a Human-in-the-Loop gate, and a live fleet\r\ndashboard. It exists to make the architecture explorable — it is a\r\n**deliberate simulation**, not a claim that these commands drive production\r\nrobots.\r\n\r\nEvery command backed by the software twin prints a `▓ SIMULATION` banner so\r\nit can never be mistaken for real capability. Run **`zelpi demo`** for the\r\nexact split, or see the table below. (`PIOS_NO_SIM_BANNER=1` suppresses the\r\nbanner.)\r\n\r\n`npx zelpi intent \"Inventory Aisle 4\"` plans with a **real LLM call**\r\n(bring your own key, or the zero-config hosted proxy) and now always prints\r\n`plan source → LLM` or `plan source → deterministic parser`, so you can tell\r\nexactly which System-2 path produced a plan.\r\n\r\n## What's real vs. simulated — read this before you rely on it\r\n\r\n| Real & verified | Simulated / not yet verified end-to-end |\r\n|---|---|\r\n| **babyros** (`lib/babyros/`) — rosbridge v2 wire protocol, verified with zelros and roslibjs clients; SLAM/EKF verified live (0.05 m fused vs 0.14 m raw) | The fleet dashboard, System 2/1/0 tick loop, Safety Broker and agent swarm — the software twin behind the `▓ SIMULATION` banner |\r\n| **HAL protocol** (`cli/hal.mjs`, `server/robot-agent.mjs`) — real WebSocket JSON wire format, e-stop/watchdog, 300+ unit tests | The \"fine-tuning on fleet experience\" step of `hub pull` — no real fleet-telemetry/RL training pipeline exists behind it |\r\n| **ROS 1/2 bridge** (`server/createRosDriver.mjs`) — verified against a real independent `rclpy` node, both directions | `perceive` / `firewall` (`cli/spe.mjs`) — deterministic, rule-based, no model call of any kind, by design |\r\n| **`zelpi intent`** — really calls an LLM (Google/OpenAI/Ollama or the hosted proxy) and labels every plan with its true source; falls back to a keyword parser, visibly, when the LLM is unreachable | Real hardware in the loop — every verification so far is sim-driver-to-sim-driver or sim-to-local-ROS-node; no physical robot has been tested yet |\r\n| **`hub install` / `hub pull`** — download real HuggingFace weights; `vla_bridge.py` runs genuine forward passes (SmolVLA, ACT, Diffusion Policy verified) | `vla_bridge.py` feeds *synthetic* camera observations — it proves the pipeline, not that a pretrained checkpoint is useful on your robot without fine-tuning |\r\n| **GPU inference** — verified on a real RTX 3060 (SmolVLA 56 s → 3.9 s/step) | One GPU model tested; NVIDIA/CUDA only — AMD/Apple accelerators unsupported |\r\n| **Genie Sim `install`/`deps`** (`sim/scripts/geniesim_install.py`, `cli/geniesim.mjs`) — verified end-to-end on real Linux (WSL2 Ubuntu 22.04) with real Docker + NVIDIA Container Toolkit + GPU passthrough all confirmed working; found and fixed 3 real bugs in the process (Windows symlink checkout, missing `python3` fallback, an unsafe upstream interactive prompt) | Genie Sim's actual Isaac Sim runtime (`geniesim up`'s Docker image build/`docker up`/`ros2 launch`, `geniesim bridge`'s live ROS round-trip) — real code, reuses `createRosDriver.mjs` unmodified, but the Docker image itself was never built: it's a large, untested pull possibly gated behind an NVIDIA NGC login, and the one GPU tested against (RTX 3060, 6 GB) is below Isaac Sim's typical recommendation |\r\n| **`zelpi transporterdemo`** (Zelantrix floor-transfer robot) — the real, unmodified `createRosDriver.mjs` genuinely drives, docks, and e-stops a simulation of that robot's documented motor spec over a real `babyros` broker; `computeLimits()` derives velocity limits from motor spec + wheel/track geometry instead of a flat placeholder | The real robot itself — no physical unit was ever connected; its actual `/cmd_vel`/`/odom` topic names, real safe speed limits, and any real hardware e-stop remain unconfirmed, see `docs/HARDWARE.md` |\r\n| **Memory layer** (`cli/memory.mjs`, `lib/memory/polygres.mjs`) — real semantic recall via Polygres (managed Postgres + pgvector) and Google `gemini-embedding-001`; verified live recalling a paraphrase sharing zero literal words with the original episode (81% cosine relevance) | Only exercised against one Polygres project so far; falls back to a local JSON file with keyword-overlap recall when `DATABASE_URL` isn't set — that path has no real semantic matching |\r\n\r\nFull detail: [`docs/HARDWARE.md`](docs/HARDWARE.md) (including a Known Gaps\r\nsection) and `npx zelpi demo`.\r\n\r\n## The CLI\r\n\r\n```bash\r\nnpx zelpi                      # interactive OS shell — boots a backend automatically\r\nnpx zelpi help                 # full command surface\r\n```\r\n\r\nHighlights beyond the quickstart: `zelros` (ROS 1/2 CLI), `zelpi hal scan`\r\n(USB/serial hardware detection + model recommendation), `zelpi hyworld` /\r\n`zelpi lingbot` (world-model integrations), `zelpi visualise` (text → \r\nsimulatable world), `zelpi mcp` (expose ZelPi to AI agents over MCP), and the\r\nconversational shell — type plain English at the REPL and it runs real\r\ncommands to answer.\r\n\r\nPoint it at a full backend (live LLM / ROS / MLflow) with `PIOS_HOST` /\r\n`PIOS_WS_URL`. Full reference: [`docs/CLI.md`](docs/CLI.md) and\r\n`npx zelpi help`. Protocol + driver-SDK docs for building on ZelPi:\r\n[`docs/PROTOCOL.md`](docs/PROTOCOL.md) and [`docs/EXTENDING.md`](docs/EXTENDING.md).\r\n\r\n## The web Observation Deck\r\n\r\nA browser dashboard for the fleet software twin (the demo-mode half):\r\n\r\n```bash\r\nnpm install\r\nnpm run dev      # → http://localhost:3000\r\n```\r\n\r\nType an intent (`Inventory Aisle 4`, `Retrieve the green box from Aisle 3`)\r\nand watch the swarm decompose it, a robot drive the floor, and the\r\nHuman-in-the-Loop gate pause a manipulation for your authorization.\r\n\r\n- **One engine, one rAF loop.** `PiOsEngine` is framework-agnostic; React\r\n  subscribes via `useSyncExternalStore` (`lib/useEngine.ts`).\r\n- **Deterministic world.** Generated from a fixed seed (`lib/world.ts`) so\r\n  reloads are reproducible.\r\n- Stack: Next.js 15 · React 19 · TypeScript · hand-rolled engine · plain CSS.\r\n\r\n## Contributing & releasing\r\n\r\nSee [`CONTRIBUTING.md`](CONTRIBUTING.md). Releases are tag-triggered\r\n(`git tag v*` → GitHub Actions tests → `npm publish`); the changelog is\r\n[`CHANGELOG.md`](CHANGELOG.md). License: [MIT](LICENSE).\r\n\r\n**Maintainers** — build & publish the lean package locally:\r\n\r\n```bash\r\nnpm run build:pkg            # → cli-dist/ (bundled engine + CLI, no web-app deps)\r\ncd cli-dist && npm publish --access public\r\n```\r\n","readmeFilename":"README.md"}