What the data shows
- 1
NVIDIA is the most documented of the 25 companies, labs and projects (8 sourced facts).
- 2
13 statements of what 12 companies and labs sell or publish, from free simulators to world models.
- 3
9 funding rounds and 8 named customer lists.
- 4
8 measured results from 7 companies and research projects on mixing synthetic with real data.
- 5
The most recent fact on record (11 Mar 2026): EqualOcean reports that Lightwheel (Light Wheel Intelligence, Beijing) closed a combined Series A++ and A+++ round totalling RMB 1 billion.
Figure 1
Robot simulation and synthetic data companies, labs and projects
Which companies and labs sell or publish simulators, synthetic data, digital twins and world models for training robots, cars and drones, who uses them, what they cost and what they do against human data?
Base: 25 companies, labs and projects, 60 facts, each linked to the page that states it (reviewed 28 Oct 2026).
Company pages, papers and filings are marked stated; what outlets and analysts report is marked reported. Results are each source's own measurement on its own tasks, so they are not compared one to one.
Credit: compiled by RobotTraining.jobs Research, Synthetic Data for Robotics: Robot Simulation Companies, Customers, Prices and Results vs Human Data, checked 28 Oct 2026.
Figure 2
Who sells or publishes robot simulation and synthetic data
Which companies and labs offer simulators, synthetic data generators, digital twins, sim assets and world models for robots, AVs and drones?
Base: 13 facts from 12 companies, labs and projects.
Credit: compiled by RobotTraining.jobs Research, Synthetic Data for Robotics: Robot Simulation Companies, Customers, Prices and Results vs Human Data, checked 28 Oct 2026.
Figure 3
Named customers and funding
Which robot makers, AV developers and carmakers use these simulators and world models, and how much have the companies behind them raised?
Base: 17 facts from 11 companies, labs and projects.
Funding stays in the currency its source gives (Lightwheel's round is in yuan).
Credit: compiled by RobotTraining.jobs Research, Synthetic Data for Robotics: Robot Simulation Companies, Customers, Prices and Results vs Human Data, checked 28 Oct 2026.
Figure 4
What synthetic data does against real data, measured
What did papers and companies measure when they added simulation or synthetic data to real robot data?
Base: 8 facts from 7 companies, labs and projects.
Each result is the source's own test, often a few tasks and small real-robot trials; read it with its own setup.
Credit: compiled by RobotTraining.jobs Research, Synthetic Data for Robotics: Robot Simulation Companies, Customers, Prices and Results vs Human Data, checked 28 Oct 2026.
Figure 5
Scale, and how labs mix simulation with human data
How much synthetic data do these systems produce, and how do labs combine it with human teleoperation and video?
Base: 16 facts from 13 companies, labs and projects.
Scale is counted in each source's own unit (trajectories, demonstrations, hours, miles or frames per second).
Credit: compiled by RobotTraining.jobs Research, Synthetic Data for Robotics: Robot Simulation Companies, Customers, Prices and Results vs Human Data, checked 28 Oct 2026.
Figure 6
Prices and market size
What does robot simulation software cost where a price is public, and how big is the market?
Base: 6 facts from 4 companies, labs and projects.
Few vendors publish prices; most sell by quote. Free licences are listed as US$0.
Credit: compiled by RobotTraining.jobs Research, Synthetic Data for Robotics: Robot Simulation Companies, Customers, Prices and Results vs Human Data, checked 28 Oct 2026.
Figure 7
Every sourced fact
What exactly has been published about each company or project?
Base: All 60 facts. "Reported" means an outlet reports it from sources the company has not confirmed.
Amounts stay in the currency and form their source gives; nothing is converted or totalled.
Credit: compiled by RobotTraining.jobs Research, Synthetic Data for Robotics: Robot Simulation Companies, Customers, Prices and Results vs Human Data, checked 28 Oct 2026.
Robotics labs ยท Fleet operators ยท Data vendors ยท Research teams
Buy the data behind this report
This report sums up records we gather ourselves, day after day:
1,392 robot training roles followed, history included
Every role on 99 employer job boards, read each day since 12 Sep 2026: its pay, its place, and the first and last day it was up.
471 apply clicks over 28 days
Which robot training roles people really apply to, by kind of work, pay and place. The clicks happen here, so no one else can count them.
25 sourced industry datasets
Funding, revenue, deals, fleets, deployments and prices across the robot training industry, each record linked to the publication it comes from.
On offer
The raw records
Every robot training role we track: title, employer, place, kind of work, pay as stated, and the days it was first and last open.
A regular feed
New and closed roles every week or month, as file drops or through the data endpoints.
A custom cut
Any figure here by country, city, kind of work, vehicle, employer or date, or your own hiring benchmarked against the market.
Need the people behind this data for your own robots? (you contract them yourself) or (we deliver the robot data).
How it was measured
Company press releases, product, documentation and pricing pages, arXiv papers and project pages from NVIDIA, UT Austin, UC San Diego, UC Berkeley and Toyota Research Institute, a Physical Intelligence co-founder's blog, ABI Research, TechCrunch, Bloomberg, EqualOcean, Verdict, Coverager, Tectonic, The Decoder and ADAS & Autonomous Vehicle International, each linked with a verbatim quote kept in the dataset. Each row carries a link to its publication and gives the number exactly as published, with no estimates or conversions. A note under every figure says what it covers.
- Sim-to-real gap
- The drop in performance when a robot policy trained in simulation meets the real world, because no simulator matches real physics, sensors and objects exactly.
- Co-training
- Training one robot model on a mixture of simulation data and real robot data at once, in a chosen ratio, rather than training in simulation and transferring.
- Synthetic trajectories
- Robot demonstrations generated by software (for example by replaying and adapting a few human teleoperation demos in simulation) instead of recorded one by one by people.
- World model
- A generative model that predicts how a scene will look and change, used to render driving or robot scenarios for training and testing (Cosmos, GAIA-3, Genie 4).
- Digital twin
- A simulated copy of a real place, robot or task built from real capture data, so training and tests in simulation match the real setting.
Limits of this data
- Built only from public sources. Anything never announced or reported is absent, and private-company figures are whatever the company or the press said, unaudited.
- Results are each paper's or company's own test, often a handful of tasks and small real-robot trials, so a 38% or 79% gain in one study does not carry over to another.
- Few vendors publish prices: most sell by quote, so the price figure holds the free licences and the list prices that are public.
- Customer lists are as each company or outlet states them (Lightwheel's as reported partners), and several date from 2022 to 2025; each record carries its own date.
Collection and classification of listings are explained on the methodology page. Freshness, completeness and consistency are tested daily in the data quality report.
Monthly editions
The live page shows the dataset as of its latest review, and new events join it once they are made public. Every finished month also gets its own edition, locked two days after month end, so a number quoted from it stays fixed.
- Live page (you are here)Latest review
Quoting this report
You may quote, chart or republish these figures under CC BY 4.0, provided you link back to this page. The records change only when their sources are reviewed again, and the date of the last review is above. For a figure that stays put, quote a monthly edition, or note the date you accessed this page.
Citation
RobotTraining.jobs (2026). Synthetic Data for Robotics: Robot Simulation Companies, Customers, Prices and Results vs Human Data (live data, 16 Nov 2022 to 28 Oct 2026). https://robottraining.jobs/research/robot-simulation-and-synthetic-data (accessed 29 Oct 2026)
BibTeX
@misc{robottrainingjobs_robot_simulation_and_synthetic_data_live,
author = {{RobotTraining.jobs}},
title = {Synthetic Data for Robotics: Robot Simulation Companies, Customers, Prices and Results vs Human Data (live data, 16 Nov 2022 to 28 Oct 2026)},
year = {2026},
howpublished = {\url{https://robottraining.jobs/research/robot-simulation-and-synthetic-data}},
note = {Accessed 29 Oct 2026},
}Keep reading
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