zeroclaw-robot-kit 0.1.0

Robot control toolkit for ZeroClaw - drive, vision, speech, sensors, safety
Documentation

ZeroClaw Robot Kit

A complete toolkit for building AI-powered robots with ZeroClaw. Designed for Raspberry Pi deployment with offline Ollama inference.

Features

Tool Description
drive Omni-directional movement (forward, strafe, rotate)
look Camera capture + vision model description
listen Speech-to-text via Whisper.cpp
speak Text-to-speech via Piper TTS
sense LIDAR, motion sensors, ultrasonic distance
emote LED expressions and sound effects

Architecture

┌─────────────────────────────────────────────────────────┐
│                 ZeroClaw + Ollama                       │
│              (High-Level AI Brain)                      │
└─────────────────────┬───────────────────────────────────┘
                      │
        ┌─────────────┼─────────────┐
        ▼             ▼             ▼
   ┌─────────┐  ┌──────────┐  ┌──────────┐
   │ drive   │  │  look    │  │  speak   │
   │ sense   │  │  listen  │  │  emote   │
   └────┬────┘  └────┬─────┘  └────┬─────┘
        │            │             │
        ▼            ▼             ▼
   ┌─────────────────────────────────────┐
   │        Hardware Layer               │
   │  Motors, Camera, Mic, Speaker, LEDs │
   └─────────────────────────────────────┘

Hardware Requirements

Minimum

  • Raspberry Pi 4 (4GB) or Pi 5
  • USB webcam
  • USB microphone
  • Speaker with amp
  • Motor controller (L298N, TB6612, etc.)
  • 4 DC motors + omni wheels

Recommended

  • Raspberry Pi 5 (8GB)
  • RPLidar A1 for obstacle avoidance
  • LED matrix (8x8) for expressions
  • PIR motion sensors
  • HC-SR04 ultrasonic sensor

Software Dependencies

# Install on Raspberry Pi OS


# Audio

sudo apt install alsa-utils pulseaudio


# Camera

sudo apt install ffmpeg fswebcam


# Ollama (local LLM)

curl -fsSL https://ollama.ai/install.sh | sh

ollama pull llama3

ollama pull moondream  # Vision model


# Whisper.cpp (speech-to-text)

git clone https://github.com/ggerganov/whisper.cpp

cd whisper.cpp && make

sudo cp main /usr/local/bin/whisper-cpp

bash ./models/download-ggml-model.sh base


# Piper TTS (text-to-speech)

pip install piper-tts

# Or download binary from github.com/rhasspy/piper/releases


# ROS2 (optional, for advanced robotics)

# See: docs.ros.org/en/humble/Installation.html

Quick Start

1. Build ZeroClaw with robot tools

# Clone and build

git clone https://github.com/zeroclaw-labs/zeroclaw

cd zeroclaw

cargo build -p zeroclaw-robot-kit --release

2. Configure

# Copy config

mkdir -p ~/.zeroclaw

cp crates/robot-kit/robot.toml ~/.zeroclaw/

cp crates/robot-kit/SOUL.md ~/.zeroclaw/workspace/


# Edit for your hardware

nano ~/.zeroclaw/robot.toml

3. Test

# Start Ollama

ollama serve &

# Test in mock mode

./target/release/zeroclaw agent -m "Say hello and show a happy face"


# Test with real hardware

# (after configuring robot.toml)

./target/release/zeroclaw agent -m "Move forward 1 meter"

Integration

This crate is currently added as a standalone workspace member. It is not auto-registered in the core runtime by default.

Use it directly from Rust:

use zeroclaw_robot_kit::{create_tools, RobotConfig};

fn build_robot_tools() {
    let config = RobotConfig::default();
    let tools = create_tools(&config);
    assert_eq!(tools.len(), 6);
}

If you want runtime registration in zeroclaw, add a thin adapter that maps this crate's tools to the project's src/tools::Tool and register it in the factory.

Usage Examples

Play Hide and Seek

User: Let's play hide and seek!
Robot:
  1. emote(expression="excited")
  2. speak(text="Okay! I'll count to 20. Go hide!")
  3. [waits 20 seconds]
  4. speak(text="Ready or not, here I come!")
  5. sense(action="scan")
  6. drive(action="forward", distance=1)
  7. look(action="find", prompt="a child hiding")
  ...

Patrol Mode

User: Patrol the living room
Robot:
  1. sense(action="scan", direction="all")
  2. drive(action="forward", distance=2)
  3. sense(action="motion")
  4. look(action="describe")
  5. [repeat]

Interactive Conversation

User: [speaks] "Hey Buddy, what do you see?"
Robot:
  1. listen(duration=5) → "Hey Buddy, what do you see?"
  2. look(action="describe")
  3. speak(text="I see a couch, a TV, and some toys on the floor!")
  4. emote(expression="happy")

Creating a Bootable USB Tarball

# Package everything needed

mkdir zeroclaw-robot-kit

cp -r target/release/zeroclaw zeroclaw-robot-kit/

cp -r examples/robot_kit zeroclaw-robot-kit/

cp -r ~/.zeroclaw zeroclaw-robot-kit/dot-zeroclaw


# Include models

mkdir -p zeroclaw-robot-kit/models

cp ~/.zeroclaw/models/ggml-base.bin zeroclaw-robot-kit/models/

# Note: Ollama models are large, may want to download on target


# Create tarball

tar -czvf zeroclaw-robot-kit.tar.gz zeroclaw-robot-kit/


# Copy to USB

cp zeroclaw-robot-kit.tar.gz /media/usb/TarBalls/

Safety Notes

  1. Test in mock mode first - Always verify behavior before enabling real motors
  2. Set conservative speed limits - Start with max_speed = 0.3
  3. Use emergency stop - Wire a physical E-stop button to the GPIO pin
  4. Supervise with children - Robot is a toy, not a babysitter
  5. Obstacle avoidance - Enable LIDAR if available, or keep confirm_movement = true

License

MIT - Same as ZeroClaw