zeroth-bot
Zeroth Bot - 3D-printed open-source humanoid robot platform for sim-to-real and RL research. Affordable entry point for humanoid robotics.
Best use case
zeroth-bot is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Zeroth Bot - 3D-printed open-source humanoid robot platform for sim-to-real and RL research. Affordable entry point for humanoid robotics.
Teams using zeroth-bot should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/zeroth-bot/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How zeroth-bot Compares
| Feature / Agent | zeroth-bot | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Zeroth Bot - 3D-printed open-source humanoid robot platform for sim-to-real and RL research. Affordable entry point for humanoid robotics.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Zeroth Bot Skill
**Trit**: -1 (MINUS - specification/verification)
**Color**: #8CC136 (Lime Green)
**URI**: skill://zeroth-bot#8CC136
## Overview
Zeroth Bot (Z-Bot) is a 3D-printed open-source humanoid robot platform designed for sim-to-real research and RL experimentation. An affordable entry point for humanoid robotics.
## Specifications
```
┌────────────────────────────────────────────────────────────────┐
│ ZEROTH BOT (Z-BOT) │
├────────────────────────────────────────────────────────────────┤
│ │
│ Height: ~40cm │
│ Weight: ~2kg │
│ DOF: 12 joints │
│ │
│ Frame: 3D printed (PLA/PETG) │
│ Actuators: Servo motors │
│ Cost: ~$500 BOM │
│ │
│ Ideal for: │
│ ├── Learning sim-to-real transfer │
│ ├── Testing RL policies at low cost │
│ ├── Educational robotics │
│ └── Rapid prototyping │
│ │
└────────────────────────────────────────────────────────────────┘
```
## Hardware BOM
| Component | Quantity | Notes |
|-----------|----------|-------|
| Servo motors | 12 | Standard hobby servos |
| 3D printed parts | Full set | STL files provided |
| MCU | 1 | ESP32 or Teensy |
| IMU | 1 | MPU6050 or similar |
| Power | 1 | 2S-3S LiPo |
## Training Pipeline
```python
from ksim.robots.zbot import ZBotConfig
from ksim import PPOTask
class ZBotWalking(PPOTask):
robot = ZBotConfig(
model_path="zbot.mjcf",
servo_config={
"kp": 50.0,
"kd": 5.0,
"torque_limit": 5.0, # Smaller than K-Bot
}
)
# Faster training due to simpler robot
training_config = {
"num_envs": 2048,
"learning_rate": 5e-4,
}
```
## GF(3) Triads
```
zeroth-bot (-1) ⊗ kos-firmware (+1) ⊗ mujoco-scenes (0) = 0 ✓
```
## Related Skills
- `kbot-humanoid` (-1): Larger flagship humanoid
- `ksim-rl` (-1): RL training library
- `kos-firmware` (+1): Firmware (kos-zbot variant)
- `urdf2mjcf` (-1): Model conversion
## Web Frontend
Z-Bot has a web-based control interface:
- Real-time telemetry visualization
- Manual joint control
- Policy deployment interface
```typescript
// From zbot-web-frontend
import { ZBotController } from '@kscale/zbot-web';
const controller = new ZBotController({
endpoint: 'ws://zbot.local:8080',
});
await controller.connect();
await controller.setJointPositions({
hip_pitch_l: 0.5,
knee_l: -0.3,
});
```
## References
```bibtex
@misc{zerothbot2024,
title={Zeroth Bot: 3D-Printed Open-Source Humanoid},
author={K-Scale Labs},
year={2024},
url={https://github.com/kscalelabs/zeroth-bot}
}
```Related Skills
jepsen-testing
Jepsen-style correctness testing for distributed systems under faults (partitions, crashes, clock skew) using concurrent operation histories and formal checkers (linearizability/serializability and Elle-style anomalies). Use when designing, implementing, or running Jepsen tests, or interpreting histories/violations.
Deterministic Color Generation via Metadata Hashing
**Status**: ✅ Production Ready
cyton-dongle
Connect and stream from OpenBCI Cyton/Daisy via USB dongle, including first-time radio channel pairing
asi-transient-agenda
Org-agenda-like transient views for ASI skill orchestration via nbb/squint + Emacs hydra
Topological Superintelligence (TSI)
Compositional AI framework using GF(3) triadic balance and category-theoretic foundations.
zx-calculus
Coecke's ZX-calculus for quantum circuit reasoning via string diagrams with Z-spiders (green) and X-spiders (red)
zulip-cogen
Zulip Cogen Skill 🐸⚡
zls-integration
zls-integration skill
zig
zig skill
zig-syrup-bci
Multimodal BCI pipeline in Zig: DSI-24 EEG, fNIRS mBLL, eye tracking IVT, LSL sync, EDF read/write, GF(3) conservation
zig-programming
zig-programming skill
zeroize-audit
Detects missing zeroization of sensitive data in source code and identifies zeroization removed by compiler optimizations, with assembly-level analysis, and control-flow verification. Use for auditing C/C++/Rust code handling secrets, keys, passwords, or other sensitive data.