plurigrid/asi

zeroth-bot

Zeroth Bot - 3D-printed open-source humanoid robot platform for sim-to-real and RL research. Affordable entry point for humanoid robotics.

First seen Jan 29, 2026

Installation

$ npx skills add plurigrid/asi --skill zeroth-bot

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npx skills add plurigrid/asi

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 62
License LICENSE
Default branch main
Open issues 3
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Version1.0.0
LicenseMIT

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 4,586 B
  • docs SUMMARY.md 156 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 7 installs

SKILL.md

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

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
// 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

@misc{zerothbot2024,
  title={Zeroth Bot: 3D-Printed Open-Source Humanoid},
  author={K-Scale Labs},
  year={2024},
  url={https://github.com/kscalelabs/zeroth-bot}
}

SDF Interleaving

This skill connects to Software Design for Flexibility (Hanson & Sussman, 2021):

Primary Chapter: 2. Domain-Specific Languages

Concepts: DSL, wrapper, pattern-directed, embedding

GF(3) Balanced Triad

zeroth-bot (−) + SDF.Ch2 (−) + [balancer] (−) = 0

Skill Trit: -1 (MINUS - verification)

Connection Pattern

DSLs embed domain knowledge. This skill defines domain-specific operations.