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Evaluate the complete robot application in the warehouse where it will work—not just the robot model or an AI demonstration. Before commissioning, document a task-based risk assessment, test routine and non-routine work in representative conditions, and agree on measurable pilot criteria. Scale only when the integrated system meets those criteria and its remaining risks are controlled.
1. Define what you are evaluating
The unit of evaluation is the installed application: the robot, payload or attachment, software and controls, sensors, fleet and warehouse-system interfaces, other equipment, people, tasks, maintenance, and operating zone. A robot specification or general AI benchmark cannot by itself show that this combination is safe or productive for your site.
Write down the intended work and the system boundary before comparing vendors. Include:
- Robot type, payload, end effector or attachment, and relevant software and control components.
- Routes, work zones, handoff points, adjacent machinery, pedestrian access, shift patterns, and expected traffic.
- Interfaces with warehouse-management, fleet-management, or other control systems.
- Operating conditions, including relevant floor, lighting, load, and communications conditions.
- Who operates, supervises, programs, maintains, or responds to the system, and what each person must do.
- Intended tasks and foreseeable misuse, including recovery and fault response.
Check whether the system is a driverless industrial truck
For AMRs and similar driverless industrial trucks, assess whether ISO 3691-4:2023 applies to the system and its use. ISO describes the standard as specifying safety requirements and means of verification for driverless industrial trucks and their systems; its examples include AMRs, automated guided vehicles, bots, automated guided carts, tunnel tuggers, and under-cart vehicles. It also notes that the condition of the operating zone significantly affects safe operation. Applicability depends on the equipment and use case, so do not assume that the label “AMR” settles it.
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The ISO listing identifies ISO 3691-4:2023 as the published second edition and lists ISO/DIS 3691-4 as a draft successor in enquiry phase. Draft status can change; verify the official listing and applicable edition during procurement and commissioning.
2. Build a task-based risk assessment
Before commissioning, identify hazards across the application and document who could be exposed, how exposure could happen, the potential severity and likelihood, and the controls selected. OSHA’s Technical Manual guidance on industrial robot systems says each robot application should have a risk assessment performed and documented before commissioning. It also cautions that an assessment alone does not ensure worker protection.
Include normal and non-routine work
Map the system’s lifecycle and tasks, not only autonomous travel. OSHA notes that many robot accidents occur during programming, maintenance, testing, setup, or adjustment. Include installation and commissioning, replenishment and handoffs, blocked-route recovery, jams, fault diagnosis, cleaning, software updates, charging or battery work where applicable, servicing, and decommissioning. Consider emergency stops and what happens when the system is restarted.
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Involve the people who know the work
Include affected workers and people who operate, program, maintain, or respond to the system. Their knowledge helps reveal informal workarounds, congestion points, and recovery tasks that may not appear in a process diagram. OSHA recommends worker participation and says integrators should document the assessment before commissioning and provide it to the employer.
Use the findings to select controls and verify them. During commissioning, review the risk assessment, installation and testing procedures, manufacturer requirements, temporary safeguards used during installation, emergency-stop requirements, and whether safeguards work as designed. Preserve test records, including checks after maintenance or service.
3. Test the integrated system in representative conditions
An empty-aisle demonstration does not establish how a system performs in a working warehouse. Design scenarios from the risk assessment and actual operating conditions. Test routine tasks as well as reasonably foreseeable failures and misuse, and record the configuration and software versions used.
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Build scenarios around the site’s risks
Depending on the application, scenarios may include people crossing or walking alongside a robot, blocked or narrowed routes, mixed traffic, variations in load, changed floor or lighting conditions, loss of communications, localization uncertainty, or a stopped or failed sensor. Also test emergency stops, restart after a stop, and how a worker safely recovers the system from a fault. These are practical scenario examples, not a universal test list or pass threshold.
Keep evidence that can be checked and repeated
For each scenario, record the test setup, relevant system configuration, observed behavior, failures, corrective actions, and retest results. Define in advance what constitutes a pass, who signs off, and what findings block commissioning. If a failure prompts a change, repeat the relevant tests on the changed configuration rather than relying on results from an earlier version.
NIST’s 2016 methodology for evaluating manufacturing mobile manipulator safety offers useful background when a system combines a manipulator with a mobile base. It does not establish that every warehouse AMR is a mobile manipulator or provide a ready-made warehouse acceptance score.
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4. Evaluate AI, safety, and operational performance
Keep three kinds of evidence distinct: robot and application safety, the AI-enabled capability, and operational outcomes. Then test how they interact in the integrated system. A useful AI framework does not replace application-specific safety assessment.
Ask what the AI can and cannot do
NIST’s voluntary AI Risk Management Framework provides a structure for considering trustworthiness across AI design, development, use, and evaluation. The NIST AI Resource Center provides testing, evaluation, verification, and validation resources. Neither source supplies a warehouse-specific acceptance benchmark.
For each AI-enabled function, ask the vendor to describe its operating envelope, known limitations, dependencies on data or configuration, and behavior when it is uncertain or cannot complete a task. Establish how failures are detected, when a person is alerted, what logs are available, and how updates and configuration changes are controlled. These are practical questions for evaluating the application, not requirements prescribed by the NIST sources.
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Set measurable pilot criteria before the pilot
Agree with the vendor on site-representative tasks, the required task and load mix, measurement methods, and pass conditions. Possible measures include:
- Task completion and throughput under the site’s required workload mix.
- Availability or uptime, with the measurement window and treatment of planned downtime defined.
- Exception frequency, human interventions, and time to recover from faults.
- Response to blocked routes and tested sensor or communications problems.
- Integration effort, worker training needs, and maintenance and support arrangements.
- Adaptability to site changes, cybersecurity and update governance, and cost under consistent operating assumptions.
These are candidate measures, not universal thresholds established by the cited sources. Compare options on the same tasks and assumptions; do not treat a vendor’s demonstration or a single performance figure as proof that the system will meet your site’s needs.
5. Decide whether to pilot, scale, or stop
A pilot is a controlled way to gather evidence, not a substitute for a risk assessment. Before it starts, document its boundaries, responsible owners, emergency response, stopping conditions, and how incidents and near misses will be recorded. Make clear who can stop the test and how the system will be left in a safe state.
Use the pilot to check the agreed criteria in representative operation. Record failures and near misses, close identified hazards, and repeat failed tests after corrective work. Scale only when the integrated application meets the pre-agreed criteria, residual risks have been addressed, and workers have been trained for their roles. If it does not, pause deployment and revise the controls, configuration, or task scope before deciding whether to test again.
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OSHA’s robotics overview states: “There are currently no specific OSHA standards for the robotics industry.” That statement does not mean that no OSHA requirements apply to a particular workplace or application. Employers still need to evaluate applicable requirements and relevant consensus standards for their equipment, tasks, and jurisdiction.
OSHA’s overview also says studies indicate many robot accidents occur in non-routine conditions, including programming, maintenance, testing, setup, or adjustment. Its Technical Manual discusses application-specific assessment, safeguards, evaluation, commissioning, and records. References on that manual page may reflect editions current when it was updated; verify current editions and legal applicability. This general guidance is not a site-specific engineering assessment or legal determination.
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