Paul Veth is a student of Physical AI, learning in public and documenting what he discovers about the actuator technology behind humanoid robots.
ActuatorHQ is built by Paul Veth, a student of the Physical AI space who started this project to make sense of the technology powering humanoid robots. Paul is not an actuator engineer or a robotics veteran. He is genuinely new to this field, learning in public, and documenting what he finds along the way. The idea behind ActuatorHQ is simple: when you study something seriously, write it down, verify it against primary sources, and share it openly, the result is often more useful than surface-level coverage. Every article is sourced, every claim is checked, and the perspective is always honest about what Paul knows and what he is still figuring out. This is a learning project that happens to produce useful analysis.
Most coverage in this space comes from insiders or hype machines. ActuatorHQ comes from a genuinely curious outsider who reads the datasheets, checks the sources, and admits when something is beyond his current understanding.

ActuatorHQ publishes in-depth, data-driven analysis of the humanoid robotics actuator market. We connect component-level specifications , torque density, backdrivability, thermal management , to system performance, company strategy, and market dynamics. Every claim is backed by primary sources, datasheets, or verifiable data. No hype.
ActuatorHQ publishes data-driven analysis of the humanoid robotics actuator market, connecting component specs to real market dynamics.
If you're an investor tracking humanoid robotics, a founder building in Physical AI, or a team that needs component-level market intelligence beyond what's publicly available , Paul Veth is open to direct conversations. ActuatorHQ doesn't do generic consulting. It does specific, rigorous analysis for people who need to get it right. Reach out and let's talk about what you're trying to understand.
Built on 23+ years of entrepreneurial experience and a rigorous, data-first approach to every analysis published on the Physical AI market.
From actuator benchmarks to company strategy teardowns, ActuatorHQ publishes intelligence that engineers and investors in Physical AI actually use.
KAIST's Humanoid v0.7 demonstrated moonwalking and soccer kicks in an outdoor field test, showcasing real-world force control and dynamic motion capabilities.
Chinese researchers achieved 96.5% accuracy in humanoid robot tennis by reducing complex human motion to simplified, learnable movement primitives that robots can reliably execute.