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Make a physical AI system safer by assessing the complete application—not just its model or robot—and combining suitable safeguards with real-world validation, ongoing monitoring, and a clear way for people to intervene or stop work. The right measures depend on the task, equipment, environment, and people who may be exposed.
Start with the application, not the AI model
“Physical AI” covers many kinds of machines and deployments; it is not the scope of a single robot-safety standard. For an industrial robot, safety depends on the robot, its end effector and load, control software, nearby equipment, workcell layout, human tasks, and operating procedures. An AI perception or decision-making component is only one part of that system.
Define the application before choosing protections. Record the task, operating modes, robot and tooling, loads, work envelope, nearby machinery, environmental conditions, and who may enter the area. Include foreseeable non-routine work: programming, setup, testing, adjustment, fault recovery, and maintenance. OSHA notes that robot accidents often occur during such conditions, which is why normal production should not be the only scenario considered in a risk assessment. See OSHA’s robotics standards and guidance.
Know which standards apply
Standards have defined scopes; a label such as “cobot” does not establish that a particular installation is safe. ISO lists ISO 10218-1:2025, the third edition published in February 2025, as requirements for the industrial robot itself. Application and integration requirements are addressed separately in Part 2, so the robot’s design alone does not settle whether a workcell is safe. The Part 1 scope excludes several uses, including medical and healthcare robots, public-access service robots, consumer products for public access, and machines for lifting or transporting people.
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ISO/TS 15066:2016 supplements ISO 10218-1 and ISO 10218-2 for collaborative industrial robot operation. ISO says it was reviewed and confirmed in 2022 and remains current. It does not apply to non-industrial robots, although its safety principles may be useful in other areas. For any deployment, verify the applicable standards edition, local adoption, and sector-specific requirements rather than assuming an industrial standard covers every physical AI system.
In the United States, OSHA states that there are currently no specific OSHA standards for the robotics industry. It lists other workplace requirements and consensus standards related to robotics, but says consensus standards are guidance from their originating organizations, not OSHA regulations. Which federal, state-plan, industry, and application-specific requirements apply depends on the workplace and deployment; an ISO standard is not automatically law in every U.S. workplace. Check current editions and jurisdictional status when determining legal obligations.
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Use a system-level risk-reduction sequence
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Map hazards and people at risk
Identify who could be exposed, how they could enter the work area, and what could go wrong in each operating mode. Examine hazards from robot motion, tooling, loads, associated equipment, and the task itself, including abnormal operations and foreseeable misuse.
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Assess the integrated application
Evaluate the robot and its complete application rather than treating the AI model as the whole system. Consider the workcell layout, human access, operating procedures, and integration with nearby equipment. Robot requirements and application/integration requirements are distinct parts of the ISO 10218 series.
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Choose safeguards for the hazards identified
Select protections that address the particular exposure and task. Physical separation, presence sensing, speed-and-separation monitoring, and power-and-force limiting control risk in different ways; they are not interchangeable. The comparison below describes their general roles, not a site-specific recommendation.
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Validate the safety functions together
Check that sensors, safety-related controls, stopping behavior, tooling, layout, and procedures work as intended under expected and reasonably foreseeable conditions. A sensor, warning, or AI perception function by itself does not demonstrate that the complete installation is safe. OSHA’s robotics guidance emphasizes risk assessment and safeguarding; integration is also addressed by ISO 10218-2.
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Plan for AI errors and uncertainty
Apply AI risk management alongside machinery and sector-specific requirements. NIST’s AI Risk Management Framework 1.0 is voluntary and non-sector-specific. It calls for context-sensitive risk management, attention to robustness and reliability, and testing or monitoring after deployment. It also identifies human intervention as a possible response when an AI system cannot detect or correct errors. NIST says risks that could lead to serious injury or death warrant the most urgent prioritization and thorough management.
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Reassess when the deployment changes
Review the risk assessment when software or models, tasks, tooling, layout, loads, operating speed, access patterns, or maintenance procedures change. Track incidents and near misses, assign responsibility for stopping and recovering the system, and ensure operators and maintainers know the applicable safe-work procedures.
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Compare safeguard approaches by what they protect against
Choose based on the hazards and the application, not on a technology label. In addition to the general role shown below, assess coverage of the full work envelope and tooling, detection and stopping performance, behavior under sensor or control failure, access for setup and maintenance, integration with other equipment, and the evidence available to validate the installation.
| Approach | General role | What to evaluate |
|---|---|---|
| Physical guarding and interlocks | Create a barrier and stop or inhibit operation when access is opened. | Whether the barrier suits the exposure and whether required setup, work, and recovery access are addressed. |
| Presence sensing | Detect a person or body part entering a protected zone and initiate a protective response. | Sensor selection and placement in relation to the hazard and the system’s stopping behavior. Warning lights or sounds alone are not safeguards. |
| Speed-and-separation monitoring | Constrain robot speed while maintaining adequate distance from a person, with the aim of preventing contact. | Whether the monitored separation and response are sufficient for the particular layout and operating conditions. See NIST’s speed-and-separation monitoring testbed work. |
| Power-and-force limiting | Limit contact forces or pressures and use protective stopping when limits are exceeded. | Whether the approach is suitable for the task and validated for the application. NIST’s 2012 publication covers measurement methods and injury metrics; it is technical background, not a substitute for current applicable standards or a site evaluation. See NIST’s blunt-force impact measurement publication. |
| AI monitoring and intervention planning | Support lifecycle risk management through testing, robustness work, deployment monitoring, and planned human intervention for errors or unexpected conditions. | How the AI-related response fits with physical safeguards and machine-safety functions; AI monitoring does not replace them. |
Make intervention and recovery part of the design
People need a defined response when the system behaves unexpectedly or cannot detect or correct an error. Specify who can stop the system, how work is made safe before recovery, and what checks are required before restarting. Include the people responsible for programming, operating, and maintaining the equipment when developing these procedures. A stop path is useful only if it is accessible, understood, and consistent with the safeguards and operating modes in the integrated application.
What the available evidence does—and does not—show
The cited sources provide industrial-robot safety guidance and a general AI risk-management framework, not one machine-specific standard for every autonomous vehicle, medical robot, public-facing service robot, consumer device, or other embodied AI system. They also do not establish a general accident rate for physical AI. OSHA’s overview refers to accidents during non-routine conditions but does not provide an attributable figure, study name, and publication year for that statement, so it should not be turned into a numerical claim.
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