Industrial humanoid in a controlled bay while dormant safety mechanisms are tested.

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A Robot Must Test the Things It Hopes Never to Use

Dormant safety functions can fail silently while robots continue productive work. This white paper examines how humanoid developers can build risk-based proof-test programmes, verify physical outcomes, maintain configuration-aware fleet evidence, and design semiconductor-enabled diagnostics. The resulting assurance depends on independent measurement, secure test authority, disciplined restoration and engineering governance.

2026-11-011 min

Humanoid with a highlighted central compute and distributed physical control networks

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Onboard Compute Is Becoming a Robot’s Qualification Anchor

Agility Robotics’ decision to standardize Digit 5 on NVIDIA IGX Thor marks a shift in humanoid architecture. Compute now connects AI capabilities to deterministic execution, safety assurance and lifecycle governance. The commercial test is whether a controlled platform can reduce qualification effort while managing faults, updates and supplier dependence.

2026-10-271 min

Standards at the Intersection technical illustration

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Who Sets the Rules for Physical AI?

Physical AI inherits existing industrial, safety and AI standards while new initiatives target humanoid capabilities, autonomous behaviour and modular interfaces. This article examines the international committees, emerging projects and diverging regional approaches across China, Europe, the United States, Japan and Korea—and evaluates what the evolving rulebook means for developers of

2026-10-261 min

Three robot architectures above shared electronic functions.

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The Hypotheses references to Forecasting Physical AI

Physical AI forecasts depend on beliefs about useful work, customer economics and adoption. Five competing hypothesis pairs explore possible futures through 2035. A practical process connects scoped assumptions, deployment evidence and scenarios to forecast revisions, helping teams prioritise research, document disagreement and learn as real operating results become available.

2026-10-191 min

Latest signals

A Robot Must Test the Things It Hopes Never to Use Onboard Compute Is Becoming a Robot’s Qualification Anchor Who Sets the Rules for Physical AI?The Hypotheses references to Forecasting Physical AI Humanoids in Logistics: Make the Robot Earn Its Shape Humanoids Get Cheaper. The Service Still Has a Price.When AI Finds a Way Around: What the Hugging Face Incident Means for Physical AI The Physical World Has No Undo Button

DXresearch archive

Latest posts

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Humanoid Robotics Electrical and Electronic Architecture

Why system architecture, not intelligence, decides whether humanoids scale Humanoid robots concentrate more actuation, sensing, and compute per kilogram than almost any other engineered…

2026-02-0110 min

Physical AI Robotics

Torque Sensing as a Control and Safety Primitive in Physical-AI Robotics

Torque sensing has transitioned from a niche capability to a foundational system primitive for physical-AI robots operating in unstructured, contact-rich environments. By exposing interaction…

2026-02-0110 min

Physical AI Robotics

Functional System Blocks of a Physical AI Humanoid

A humanoid Physical AI system is not defined by its shape, but by the tight coupling of perception, intelligence, control, actuation, energy, and safety…

2026-01-316 min

Physical AI Robotics

What Is Physical AI?

Physical AI refers to embodied systems that sense, decide, and act in the real world using a combination of learning-based intelligence and deterministic physical…

2026-01-315 min

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From Classical Robotics to Physical AI

The transition from classical robotics to Physical AI represents a structural change in how intelligence, control, and uncertainty are handled inside robotic systems.…

2026-01-316 min