What is the K-Scale Robotics skill?

It is a specialized Claude Code skill that indexes the K-Scale Labs ecosystem, providing tools for building, training, and deploying humanoid robots.

Does this skill support physical hardware deployment?

Yes, it includes the KOS firmware and kscale-actuator services, which facilitate gRPC-based control of physical robot hardware and CAN-based motors.

What type of machine learning models are compatible with K-Scale?

The ecosystem supports Reinforcement Learning (RL) for locomotion (ksim-rl) and Vision-Language-Action (VLA) models for perception and manipulation.

Is the K-Scale robotics stack open-source?

Yes, the entire K-Scale stack is open-source and licensed under the MIT license, encouraging community contribution and customization.

Which physics engine does K-Scale utilize?

K-Scale primarily uses MuJoCo for scene composition and high-fidelity physics simulation, supported by tools like urdf2mjcf for model conversion.

K-Scale Robotics Ecosystem

Name: K-Scale Robotics Ecosystem
Author: plurigrid

byplurigrid

•

データサイエンスとML

Provides a comprehensive open-source framework for building, training, and deploying humanoid robots using reinforcement learning and sim-to-real transfer.

The K-Scale skill is a unified robotics development stack designed to streamline the creation of humanoid robots through a specialized collection of sub-skills. It integrates Reinforcement Learning (RL) training via ksim-rl, scene composition in MuJoCo, and hardware deployment through the KOS (K-Scale Operating System) firmware. By following a GF(3) triadic organization, the skill ensures architectural balance between generation, coordination, and analysis, making it an essential tool for developers working on humanoid locomotion, vision-language-action (VLA) models, and low-level actuator control via CAN and gRPC.

主な機能

01Automated sim-to-real transfer using entropy-driven domain randomization.

02Unified index for humanoid robot development, training, and deployment.

03Native gRPC integration for low-latency robot firmware and actuator control.

048 GitHub stars

05High-fidelity scene composition and physics simulation using MuJoCo.

06Reinforcement Learning (RL) pipelines for locomotion and manipulation tasks.

ユースケース

01Training humanoid locomotion policies in high-fidelity simulation environments.

02Converting URDF robot models to MJCF format for advanced physics simulation.

03Deploying pre-trained AI models to physical robot hardware via KOS firmware.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add plurigrid/asi kscale

For use in Claude.ai and ChatGPT

Download Skill