EAI2 - OPERATING GUIDE

Embodied AI,
from study to field work.

Use one route to learn the robotics stack, design data-collection rigs, and map the companies building physical intelligence.

18-step learning route Robot data-collection methods Global company and supply-chain map
Start the route Build a data rig Read the company map
19 Articles
3 Assets
118 Pages
Image: Unitree G1

What are you trying to solve?

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01 Build your embodied AI foundation Move from robotics basics through perception, control, and real deployment. 02 Design a robot data loop Plan sensors, teleoperation, quality checks, and dataset versions. 03 Understand companies and industry layers Compare company roles by region, supply chain, and application area.

Field assets

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Robot Intelligence 5 articles Hardware 3 articles Tools 5 articles Industry 5 articles Field Notes RSS archive Regions global signals

What you can do here

Move from reading about robots to making better technical decisions.

10 min Choose your next learning step Know whether to study perception, control, policy learning, or deployment next. 30 min Sketch a data-collection rig Pick sensors, teleop method, QA loop, and a starter kit for one task. 45 min Understand a company layer Separate robot bodies, sensors, actuators, algorithms, and application companies.

Workbench

Three connected views of the same field

Course Move from core concepts to perception, control, learning, and real deployment. A practical engineering route for deciding what to learn next. Data Covers teleoperation, sensors, QA, and dataset versioning. Use it to design the smallest useful data loop for one task. Map Compare representative companies by region, supply-chain layer, and category. Turns company information into a practical market view.
Editorial policy Source standards, AI disclosure, corrections, and advertising independence. By EAI2 Editorial Independent technical coverage of embodied AI and humanoid robotics. Corrections welcome Send source-backed corrections, tips, or coverage suggestions.
Learning route Turn robotics knowledge into next actions Follow concepts, perception, control, learning, and deployment as one path. Industry map Understand who builds the robot stack Compare company roles by region, supply-chain layer, and application area. Regional watch Track embodied AI signals beyond China and the U.S. Follow local strengths in Japan, Korea, Germany, the Middle East, and more.

All Articles

Featured below, then everything else by date.

★ Featured
Fundamentals

Getting Started with Embodied AI in 2026: A Practical Guide for Engineers

A hands-on guide for software engineers who want to break into embodied AI — covering the key concepts, tools, frameworks, and a concrete learning path.

5 min read · Apr 14, 2026 Read article →
Tools & Frameworks

5 Robot Learning Frameworks You Should Know in 2026

A practical overview of the top robot learning frameworks in 2026 — what each does best, when to use it, and how they fit together.

4 min read · Apr 11
Robot Intelligence

Sim-to-Real Transfer in 2026: Why Your Robot Policy Breaks in the Real World (And How to Fix It)

A practical guide to bridging the sim-to-real gap — why policies trained in simulation fail on real robots, and the proven techniques to fix it.

5 min read · Apr 13
Tools & Frameworks

LeRobot Tutorial: Collect Data and Train Your First Robot Policy

A step-by-step tutorial for using Hugging Face LeRobot to collect demonstration data, train an imitation learning policy, and deploy it on a simulated robot.

8 min read · Apr 7
Tools & Frameworks

Edge AI for Robots: Running VLA Models on Jetson, NPUs, and Mobile Hardware

How to deploy VLA and robot learning models on edge hardware — from NVIDIA Jetson to mobile NPUs — with practical optimization techniques for real-time robot control.

4 min read · Apr 3
Tools & Frameworks

Robot Data Collection Methods Compared: From Teleoperation to Autonomous Self-Improvement

How modern robotics teams collect training data — covering teleoperation rigs, kinesthetic teaching, third-person video, simulation rollouts, and autonomous data flywheels. With cost and quality trade-offs.

8 min read · Apr 27
Robot Intelligence

Reinforcement Learning for Robotics in 2026: What Actually Works

A practical guide to reinforcement learning for robots in 2026 — which algorithms work, which environments to use, and the techniques that bridge from simulation success to real-world deployment.

5 min read · Apr 17
Tools & Frameworks

ROS 2 for Modern Robotics: Why It Still Matters in the Age of Foundation Models

ROS 2 isn’t going anywhere. Here’s why it remains the connective tissue of real-world robotics in 2026, even as VLA models reshape how robots think — and how to use it without drowning in complexity.

6 min read · Apr 17
Robot Intelligence

VLA Models Compared: GR00T N1 vs pi0 vs OpenVLA in 2026

A detailed comparison of the three leading Vision-Language-Action foundation models for robotics in 2026 — NVIDIA GR00T N1, Physical Intelligence pi0, and the open-source OpenVLA.

5 min read · Apr 16
Robot Hardware

The Humanoid Robot Landscape in 2026: Who's Shipping and Who's Still Demoing

A no-hype overview of the humanoid robot industry in 2026 — separating companies that are actually shipping units from those still producing demo videos.

4 min read · Apr 15