Humanoid Training · Part of The Humanoid Group

About Humanoid Training

Humanoid Training is a plain-language guide to how humanoid robots are taught, tested and handed over to the people who work beside them, written by the editorial team at The Humanoid Group.

Sources we rely on

OSHA Technical Manual, Section IV, Chapter 4: Industrial Robot System Safety — US Occupational Safety and Health Administration (OSHA).
Sets out the safety training OSHA expects for people who program, operate and maintain robots, including proof of competency.
Robotics in the Workplace: An Overview — NIOSH, US Centers for Disease Control and Prevention.
How industrial, service and collaborative robots change workplace hazards, and what NIOSH studies about working beside them.
Advanced robotics and artificial intelligence for the automation of tasks at work: current status and considerations for OSH — European Agency for Safety and Health at Work (EU-OSHA).
EU-OSHA research on where AI and advanced robots automate tasks at work, with a taxonomy and the policies that apply.
Grasping, Manipulation, and Contact Safety Performance of Robotic Systems — National Institute of Standards and Technology (NIST).
Test methods, task boards and metrics NIST is developing to measure robot grasping, dexterity and contact safety.
ISO/IEC 5259-1:2024 Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 1: Overview, terminology, and examples — International Organization for Standardization (ISO) and IEC.
Opening part of the ISO/IEC 5259 series on assessing and improving the quality of data used to train machine learning models.
Recent Advances in Robot Learning from Demonstration — Annual Review of Control, Robotics, and Autonomous Systems.
Peer-reviewed survey of imitation learning methods, when demonstrating beats scripting, and the problems still open.
Robot Learning From Randomized Simulations: A Review — Frontiers in Robotics and AI.
Peer-reviewed review of sim-to-real work: why the reality gap appears and how randomising the simulator helps policies transfer.
Real-World Humanoid Locomotion with Reinforcement Learning — UC Berkeley (arXiv; published in Science Robotics).
A humanoid walking controller trained entirely in varied simulations, then run on the real robot without fine-tuning.

Learning From Demonstration — How humanoids learn skills from human demonstrations and teleoperation data.
Simulation & Sim-to-Real — Why humanoids train in simulation first, and what it takes to cross the gap to the real world.
Evaluation & Readiness — How to judge whether a humanoid is safe, reliable and ready for real work.
Preparing Your Team — The roles, skills and habits your organisation needs before humanoids arrive.
Humanoid Training Services — When to outsource robot data collection, teleoperation and evaluation, and what to ask a provider.
How to Train a Humanoid — A plain-language walkthrough of teaching a humanoid a new task, from demonstration to testing.
Teleoperation for Data — VR, leader-arm and exoskeleton rigs for recording humanoid demonstrations, and what makes a run worth keeping.
Learning to Walk — How reinforcement learning teaches humanoids to walk and balance in simulation before they step out for real.
Training Data and Privacy — Recording people at work or at home to train robots: consent, data protection law and careful data handling.
Choosing First Tasks — How to pick a humanoid's first skills, set pass marks and budget for the demonstrations each one needs.
Safety While Training — Zones, stops and supervision that keep people safe while a humanoid is being taught, tested and debugged.
Latest updates — Teaching robots now takes data operations, simulation and careful testing. These figures and dated updates show where training data comes from, how fast robots learn new tasks and how results are checked.
About us — What we cover, how we source every figure, and who publishes this site.

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