Mini+ Agent Kit

Drive a BitRobot-compatible ground robot with Claude — an Earth Rover Mini+ or a Waveshare UGV — and turn its runs into Verifiable Robotic Work on-chain.

It's built on the three real specs in the BitRobot ecosystem, not bespoke glue:

Architecture

📐 Full system architecture with 13 validated diagrams, control equations, and the capability matrix: docs/ARCHITECTURE.md.

            instruction files (AGENTS/SOUL/IDENTITY/TOOLS) ── compose ──► system prompt
                                                                              │
 Claude (Opus 4.8) ──► openClaw VERBS (tools) ─────────────────────────────► RoverVerbs
   status_report · look · photo · move · turn · obstacle_check · track_color ·   │   │
   autonav · navigate · checkpoint_reached · speak · set_lamp · camera_move ·    │   │
   capture_work · finish                                                         │   │
                                                                ┌───────────────┘   └───────────────┐
                                                       EarthRoverVerbs                       HarnessVerbs
                                                  (delegates to openClaw                (closed-loop turn via yaw,
                                                   server /turn /track-color…)           lidar obstacle_check…)
                                                          │                                     │
                                                  EarthRoverClient                        HarnessClient
                                                  (FrodoBots SDK)                         (robot-harness, Waveshare)

 capture_work ─► store_artifact (Walrus URL + IPFS CID + sha256) ─► WorkSink
                                                                     ├─ BitRobotSink   → /subnets/{id}/events (VRW → Bolts)
                                                                     └─ OnchainRoverSink → sidecar /proof → settle.ts (Arc/Solana)

One agent, two robots (swap the client), one artifact, two ledgers.

Related MCP server: Robotics MCP Server

Why verbs, not raw control

The openClaw kit's key lesson: an agent should drive through safe, high-level verbs, never raw /control. So turn uses heading feedback (and is the only way to rotate), move is distance-calibrated and aborts on a blocked path, status_report returns real sensors (never fabricated), and track_color / autonav hand off to purpose-built loops — exactly the two flagship demos ("send stats via chat", "find and follow the yellow card"). The agent's behavior comes from editable markdown in instructions/.

Install

pip install -e .                  # core
pip install -e ".[mcp]"           # + expose the rover as an MCP server
pip install -e ".[track]"         # + Waveshare client-side track_color (Pillow+numpy)
pip install -e ".[lerobot]"       # + Waveshare LeRobot backend (datasets/policies)
pip install -e ".[vision]"        # + Gemini scene captions for the harness
cp .env.example .env              # fill in keys

You also need a robot backend running:

• Earth Rover: the Earth Rovers SDK (feature/openClaw) — hypercorn main:app (:8000)

• Waveshare: your robot-harness (or the sidecar adapter) (:8000)

Quick start — Claude drives, work goes on-chain

from mini_plus_agent_kit import HarnessClient, MiniPlusAgent, BitRobotSink, OnchainRoverSink, MultiSink

rover = HarnessClient("http://localhost:8000", speed_mode="medium")   # Waveshare
work  = MultiSink(BitRobotSink(), OnchainRoverSink())                 # VRW + your settle
agent = MiniPlusAgent(rover, work=work, resource_name="ugv_001", on_event=print)

result = agent.run(
    "Explore the room, find the package, capture_work it as proof, then finish. "
    "Check obstacles before moving forward."
)

Swap HarnessClient(...) for EarthRoverClient(...) and the same agent drives an Earth Rover Mini+ (gaining speak and a server-side blocking turn). The toolset auto-adapts to each backend's verb capabilities. track_color ("follow the yellow card") works on both — server-side on the Earth Rover, and as a client-side HSV visual-servo loop on the Waveshare ([track] extra: Pillow+numpy).

Drive from any MCP client (the elegant core)

The bundled agent and Telegram bridge are conveniences — the standard way to drive the rover is as an MCP server. Point any MCP client (Claude Desktop, Claude Code, Cursor, the Agent SDK) at it and the verbs become its tools — no kit-specific agent loop:

mpak mcp --backend waveshare         # stdio MCP server (verbs as tools)

// Claude Desktop / Code config
{ "mcpServers": { "rover": { "command": "mpak", "args": ["mcp", "--backend", "waveshare"] } } }

Crucially this isn't a fourth code path: the MCP tool list is make_tools(...) and each call routes through dispatch(...) — the same single source of truth the Claude agent and the Telegram chat use. One verb definition, three front-ends (agent / chat / MCP), every robot backend.

CLI

mpak mission "Find and follow the yellow card." --backend earthrover --bitrobot
mpak mission "Patrol and flag obstacles."        --backend waveshare  --onchain --bitrobot
mpak telegram --backend waveshare                # chat-drive the rover (openClaw demo)
mpak register ugv_001 --backend waveshare --owner <SOL>   # BitRobot Entity NFT
mpak mcp --backend waveshare                     # serve as an MCP server (see above)
mpak status            # telemetry + mission state
mpak checkpoints       # list mission checkpoints (Earth Rover)
mpak shot --map -o frames/                       # save camera frames
mpak speak "hello"     # text-to-speech (Earth Rover)
mpak teleop            # manual keyboard driving

Chat surface (Telegram — the openClaw flagship demo)

RoverChat is a conversational agent over the same verbs; TelegramBridge long-polls the Bot API and pipes messages through it, replying with text and inline camera frames.

from mini_plus_agent_kit import HarnessClient, TelegramBridge
bridge = TelegramBridge(HarnessClient("http://localhost:8000"),
                        token="<TELEGRAM_BOT_TOKEN>")
bridge.run_forever()      # "what's your status?" → status_report; "look" → photo inline

Or just mpak telegram --backend waveshare (reads TELEGRAM_BOT_TOKEN + ANTHROPIC_API_KEY). Add --bitrobot/--onchain to record VRW from chat-driven runs.

Verifiable Robotic Work

capture_work (or submit_work) stores the frame once and runs the task lifecycle on whichever sink(s) you configured:

from mini_plus_agent_kit import submit_work, BitRobotSink
rec = submit_work(BitRobotSink(), open("clip.jpg","rb").read(),
                  label="delivery @ door", vrw_points=120, resource_name="frodobot_001")
print(rec.artifact.ipfs_cid, rec.artifact.walrus_url)

• BitRobotSink → register_resource → task_start → task_end {raw_data_uri, raw_data_cid} → task_validate {vrw_points} (Subnet Points → Bolts; Entity NFT on Solana). raw_data_uri is the Walrus URL; raw_data_cid is computed (cid_v1_raw for ≤1 MiB, the ipfs CLI for larger).

• OnchainRoverSink → task_end posts /proof {blobId, sha256, label} (the tracker); task_validate posts /give-feedback {robot, skill, score, blobId, sha256}, which your sidecar (index.ts:597) anchors on Arc via settle.giveFeedback → ReputationRegistry.giveFeedback. The robot's on-chain agentId is resolved sidecar-side; key custody stays in the sidecar. OnchainRoverSink(robot="guard", skill="deliver", score=None, anchor=True) — VRW points map to the 0–100 reputation score unless you pass an explicit score; set anchor=False to register the proof without the chain write. (The kit sends the bare hex sha256 since giveFeedback re-adds 0x.)

• RaceProofSink(winner_idx=..., race_id=None) → task_validate posts /race/settle {raceId, winnerIdx, sha256, blobId} → settle.settleRaceOnChain → RaceMarket.settle (judge = guard). Use when the agent is the race oracle and its captured finish frame should settle the parimutuel market (unlike /race/finish, which re-captures the guard's own photo). Needs the small POST /race/settle route added to the sidecar (mirrors /give-feedback). race_id=None lets the sidecar use its current onChainRaceId.

Register a robot as an Entity NFT (earn VRW under its own resource)

mpak register ugv_001 --backend waveshare --owner <SOLANA_WALLET> --symbol UGV

from mini_plus_agent_kit import BitRobotSink
sink = BitRobotSink(resource_subtype="waveshare_ugv", resource_name="ugv_001", owner="<sol>")
sink.register(symbol="UGV", description="Waveshare UGV", image="https://…/ugv.png")
# every subsequent submit_work/capture_work on `sink` attributes VRW to ugv_001

BitRobotSink carries resource_name/resource_subtype defaults so all work auto-attributes to the registered Entity NFT (Waveshare → waveshare_ugv, Earth Rover → frodobot).

Earth Rover Challenge (Urban track) — Claude as a navigation policy

The Earth Rover Challenge (IROS 2026) runs off-board policies that take the rover's camera + GPS and drive to mission checkpoints within a 15 m tolerance, scored by difficulty × completion time — pitting autonomous policies against human teleoperators (current AI ceiling ~57%). This kit is a challenge-ready off-board policy (it speaks the same Remote Access SDK), with real GPS waypoint navigation:

• navigate — great-circle distance, bearing, and signed turn to the next checkpoint from live GPS + heading (geo.py: haversine + initial bearing + heading error; verified against the Berkeley→Stanford route).

• checkpoint_reached — claim arrival within tolerance.

• EarthRoverVerbs.goto_checkpoint() — a deterministic turn-to-bearing + creep controller (the autonomous baseline), or let Claude drive via navigate + look + move/turn (the VLM-agent baseline — vision handles obstacles GPS can't see). See examples/earth_rover_challenge.py.

The live test drives a 2D kinematic rover sim over real HTTP to a GPS checkpoint (tests/live/test_live_navigate.py).

Waveshare as a LeRobot robot

lerobot-record --robot.type=waveshare_ugv --teleop.type=keyboard_rover \
    --dataset.repo_id=you/ugv-nav --dataset.single_task="Navigate"

WaveshareUGV presents the Mini+ action/observation schema (plus lidar) so datasets and policies are cross-compatible with the upstream EarthRover Mini+.

Layout

mini_plus_agent_kit/
  client.py          EarthRoverClient   — FrodoBots SDK transport (+ openClaw verbs)
  harness_client.py  HarnessClient      — Waveshare robot-harness transport
  rover.py           RoverVerbs         — openClaw verb surface (2 backends)
  work.py            WorkSink           — BitRobot VRW + onchain-rover, artifacts, IPFS CID
  agent.py           MiniPlusAgent      — Claude loop + instruction-file prompt
  tools.py           verb tools + dispatch
  telegram.py        RoverChat + TelegramBridge — chat surface (openClaw demo)
  mcp_server.py      MCP server over the same make_tools()+dispatch() core
  lerobot_backend.py WaveshareUGV       — LeRobot robot (optional)
  instructions/      AGENTS/SOUL/IDENTITY/TOOLS.md
  cli.py             mpak

Tests

A hermetic suite (no robot, no network, no real SDKs — httpx/anthropic are stubbed) covers kinematics, telemetry mapping, IPFS CID, capability-filtered tools, the openClaw verb→endpoint wiring, all three work sinks, and a full scripted agent-loop run:

python3 tests/run_all.py     # zero-dependency runner  → 36 passed
pytest tests/                # also works (conftest applies the same stubs)

And a live suite using real libraries and real I/O — no stubs (a local HTTP server emulates the harness; Walrus is a public testnet; no robot or keys needed):

bash tests/live/run_live.sh   # installs real deps (httpx, mcp, Pillow, numpy) into .venv, then runs:
#  • real HarnessClient/HarnessVerbs over real sockets (twist→diff on the wire,
#    telemetry/lidar, JPEG bytes, closed-loop turn, /light, /camera/move mapping)
#  • the real MCP server: real protocol (initialize→list_tools→call_tool)→dispatch→HTTP
#  • real track_color: HSV blob detection + visual-servo steering on generated frames
#  • real GPS navigate: the goto_checkpoint controller reaches a checkpoint in a sim
#  • real Walrus testnet store + byte-identical retrieve + IPFS CIDv1

Safety

turn uses heading feedback; move aborts on a lidar-blocked path; the agent is prompted to avoid people/traffic/ledges and to obstacle_check before advancing; the loop stops the robot on exit and on any verb error. This is research/hobbyist tooling — keep a human in the loop.

Sources

• bitrobot.ai/miniplusagentkit · docs.bitrobot.ai

• Earth Rovers SDK — openClaw branch

• LeRobot EarthRover Mini+

MIT.