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Figure 02, Apptronik Apollo and Hexagon Robotics AEON are the clearest humanoid platforms to evaluate for factory automation today. Figure 02 has the strongest publicly quantified production record: BMW says a 2025 deployment at Spartanburg supported more than 30,000 X3 vehicles, moved over 90,000 components and ran for about 1,250 hours. Apollo has a documented Mercedes-Benz pilot for intralogistics, kitting and inspection. AEON is BMW’s newer Leipzig platform for battery and component work, with testing staged through 2026.
None should be treated as a universally available, interchangeable appliance. Public evidence describes site-specific pilots, qualification stages and a planned move from teleoperation toward autonomy. A factory buyer should select by task, cell design, safety case, integration effort and measured operating data—not by humanoid appearance.
Which humanoid robots have real factory evidence?
Three platforms have the most defensible public evidence for industrial evaluation:
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| Platform | Factory and date | Documented work | Publicly stated specifications or results | Maturity indicated by the source |
|---|---|---|---|---|
| Figure 02 (Figure AI) | BMW Plant Spartanburg, United States; tests in 2024 and a production deployment reported in 2025 | Removing and positioning sheet-metal parts for welding in a body shop | Approximately 170 cm tall, 70 kg, 20 kg load capacity, 16 active degrees of freedom per hand; more than 90,000 components moved, approximately 1.2 million steps and around 1,250 operating hours in the 2025 deployment | One unusually quantified automotive production pilot; not proof of universal reliability |
| Apollo (Apptronik) | Mercedes-Benz Berlin-Marienfelde Digital Factory Campus; agreement announced March 2024, testing reported March 2025 | Component and module delivery, assembly-kit and tote delivery, initial quality checks and production-data collection | Approximately 5 ft 8 in tall, 160 lb, 55 lb lift capability; force control intended for operation around people | Commercially announced pilot, with teleoperation and augmented reality used to transfer knowledge before autonomous operation |
| AEON (Hexagon Robotics) | BMW Plant Leipzig, Europe; presented June 2025, initial test planned for December 2025, another test for April 2026 and a summer 2026 pilot | High-voltage battery assembly and component manufacturing, including exterior-part work | Human-like body designed for interchangeable hands, grippers and scanning tools; dynamic use on wheels | Emerging platform in staged tests; public sources do not establish production results from the planned pilot |
The distinction between “factory evidence” and “general availability” matters. BMW and Mercedes-Benz have put these systems into controlled industrial workflows, but the public announcements do not establish a standard catalog configuration, cross-site uptime, independent safety certification, total cost of ownership or a guaranteed delivery schedule.
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Figure 02: the strongest quantified production example
What BMW tested
BMW’s September 11, 2024 account describes Figure 02 at Plant Spartanburg as a roughly 170-centimetre, 70-kilogram humanoid with a 20-kilogram load capacity. In a real body-shop environment, it inserted sheet-metal parts into special fixtures. BMW also reported three times the computing power of the predecessor, improved voice communication, a stronger battery and 16 active degrees of freedom in each hand.
The task is a useful example of where a humanoid can be justified: parts must be picked, oriented and placed accurately in a workspace built for people. The robot is not simply carrying a box. It must repeat a positioning motion, maintain the required orientation and hand the part to a downstream welding process without disrupting takt time.
What the 2025 deployment measured
BMW’s later production report says Figure 02 supported production of more than 30,000 BMW X3 vehicles during a 2025 Spartanburg deployment. Over the reported operating period, it moved more than 90,000 components, covered approximately 1.2 million steps, worked around 1,250 hours and ran ten-hour shifts from Monday through Friday. BMW identifies the operation as precise removal and positioning of sheet-metal parts for welding.
Those figures are valuable because they describe sustained activity rather than a demonstration video. They still represent one robot program at one plant. They do not provide a universal cycle time, mean time between intervention, first-pass yield, injury rate or cost per part. Ask for those measures in the exact cell under consideration.
Integration lessons from Spartanburg
BMW says the pilot required early participation from production IT, occupational safety, process management and shop-floor logistics. That is a practical warning for any buyer: the robot is only one component of the automation project. Network access, production scheduling, material presentation, emergency procedures, worker training and recovery from a misplaced part must be designed together.
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Apollo: an intralogistics-first approach at Mercedes-Benz
Documented use cases
Mercedes-Benz reported on March 18, 2025 that it was testing Apollo at the Berlin-Marienfelde Digital Factory Campus. The initial use cases are repetitive intralogistics tasks: transporting components or modules to the line for skilled employees, delivering assembly kits and performing initial quality checks. Apollo also collected production data for defined MO360 use cases.
Apptronik’s March 15, 2024 announcement called the Mercedes-Benz agreement Apollo’s first publicly announced commercial deployment. It describes delivery of assembly kits and totes containing kitted parts, component inspection and movement of materials to the line. Apptronik states an approximate height of 5 feet 8 inches, a weight of 160 pounds and a 55-pound lift capability.
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Mercedes-Benz says employees transferred production knowledge through teleoperation and augmented reality, with autonomous operation described as the next step. This sequence is important when evaluating a proposal. A robot may appear autonomous during a short demonstration while still depending on human intervention for edge cases, new part variants or recovery from a blocked route.
Require the vendor to report the intervention rate, who performs interventions, how quickly a task can be resumed and whether teleoperation requires a specialist on site. Also clarify whether teleoperated data becomes part of the customer’s production model and who may reuse it.
Where Apollo may fit best
Apollo’s public Mercedes-Benz work points to facilities where the primary bottleneck is repetitive material handling rather than high-speed manipulation. A line-side delivery route, kit replenishment loop or basic inspection station can be easier to validate than a task requiring complex force interaction. The 55-pound lift figure is a rated capability cited by Apptronik; it should not be treated as the safe payload for every posture, reach distance or walking condition. Validate the complete load, gripper and route combination.
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AEON: BMW’s Leipzig platform for batteries and components
Planned production scope
BMW says Hexagon Robotics’ AEON was presented in June 2025. BMW described an initial test deployment in December 2025, another test scheduled for April 2026 and a pilot planned for summer 2026 at Plant Leipzig. The stated work covers high-voltage battery assembly and component manufacturing, including exterior-part production.
AEON’s design emphasizes a human-like body with interchangeable hands, grippers and scanning tools, plus dynamic use on wheels. That combination suggests a platform intended to move among more than one operation instead of remaining permanently fixed in a single guarded cell.
How to interpret the timeline
The announcement establishes a staged evaluation plan, not completed production performance. It is reasonable to ask BMW or the supplier for results from each gate—test objectives, achieved tasks, intervention counts, safety findings and pilot acceptance criteria—but public information does not establish those outcomes. Treat AEON as an emerging candidate for a structured pilot, especially where tool changes and mobility are central requirements.
How the platforms compare for a factory project
| Decision factor | Figure 02 | Apollo | AEON |
|---|---|---|---|
| Best-supported task | Millimetre-level sheet-metal removal and placement for welding | Intralogistics, kit and tote delivery, initial inspection | Battery assembly and component manufacturing are the stated targets |
| Published load figure | 20 kg load capacity | 55 lb lift capability | Not stated in the cited BMW announcement |
| Hand or tool detail | 16 active degrees of freedom per hand | Force control is described; hand degree-of-freedom count not stated | Interchangeable hands, grippers and scanning tools |
| Mobility detail | Production deployment data is reported; mobility specification not stated | Factory transport use case is reported; detailed route limits not stated | Dynamic use on wheels is described |
| Autonomy evidence | Production pilot operating data is reported | Teleoperation and augmented reality used for knowledge transfer; autonomous operation identified as next step | Staged testing and pilot plan; public autonomy metrics not stated |
| Public commercial terms | Not stated | Not stated | Not stated |
The table is a screening aid, not a performance ranking. A 20-kilogram capacity does not make Figure 02 better for a kit-delivery route, and a 55-pound lift rating does not prove Apollo can safely handle every component in that range. The winning platform is the one that meets the complete task specification with acceptable intervention and safety performance.
A practical evaluation process for buyers
1. Define the task at cell level
Document part mass, dimensions, center of gravity, presentation height, grasp points, cycle time, walking distance, tolerances, variant count and failure consequences. Separate sheet-metal positioning, tote movement, inspection, battery assembly and component work; they impose different dexterity and safety requirements.
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2. Demand a task-level demonstration
Provide representative parts, fixtures, packaging and route constraints. Measure completed cycles, placement accuracy, successful grasps, intervention frequency, recovery time and quality rejects. A generic pick-and-place demonstration cannot validate a battery module or a flexible sheet-metal fixture.
3. Check payload and dexterity together
Compare the rated payload with the end effector, wrist orientation, reach and walking state. For Figure 02, verify how the 20-kilogram figure applies to the proposed posture. For Apollo, test the 55-pound lift capability with the actual tote or component and required clearance. For AEON, obtain the missing payload and tool specifications before approving a pilot.
4. Build the safety case around the exact cell
Review force control, speed and separation limits, emergency-stop behavior, safe states after a power or network failure, guarding, pinch points, dropped-load scenarios and human-robot handoffs. Include risk assessment, worker training, lockout procedures and maintenance access. “Designed to work around people” is not a substitute for a documented site risk assessment.
5. Plan autonomy and intervention explicitly
Ask what happens when a part is missing, a tote is misplaced, a barcode cannot be read or a person enters the route. Record whether the robot stops, requests remote help or falls back to a safe manual procedure. For systems trained through teleoperation, establish who owns the data, how it is secured and how new variants are approved.
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Map interfaces to manufacturing execution, material control, quality records, fleet management, safety PLCs and wireless networks. BMW’s qualification approach moves from theoretical assessment to laboratory evaluation, real-world test deployment and pilot. Use similar gates, with measurable exit criteria at each stage.
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- AI Large Model ChatGPT Integration for Enhanced User-Machine Interaction. TonyPi incorporates a multimodal model, with ChatGPT at the core of its interaction system. With AI vision and voice integration, TonyPi excels in perception, reasoning, and action, enabling advanced embodied AI applications and delivering a seamless, intuitive human-machine interaction experience!
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7. Negotiate evidence-based acceptance
Require a pilot plan that names shifts, hours, throughput, uptime, intervention counts, quality targets, maintenance response and spare-part availability. Separate supplier demonstrations from customer-accepted production performance. Prices and standard contract terms are not published in the cited announcements, so confirm whether the proposal is a purchase, lease or robotics-as-a-service arrangement and define software-update, support and data-ownership terms.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Are humanoid robots commercially available or still pilots?
The most accurate answer is “commercially announced pilots and staged deployments.” Apptronik and Mercedes-Benz describe Apollo as a commercial agreement, but the reported Berlin work is still a test program using teleoperation and augmented reality before autonomous operation. BMW reports substantial Figure 02 production activity at Spartanburg, yet describes it as a pilot and does not publish a universal availability or reliability guarantee. BMW’s AEON announcement describes tests and a planned Leipzig pilot rather than a completed, repeatable production rollout.
That maturity level can still be useful. A pilot can reveal whether a human-scale robot reduces ergonomic strain, fills a labor gap or handles a task that is difficult to automate with fixed equipment. It should not be sold internally as proof that every factory, shift pattern or product variant is ready for unattended humanoid operation.
Questions to put in the request for proposal
- Which exact task has the supplier demonstrated with parts and fixtures comparable to ours?
- What are measured cycle time, placement or inspection accuracy, intervention rate and recovery time?
- What payload applies while standing, walking, reaching and using the proposed tool?
- What safety functions are built in, and which safeguards must the plant add?
- How is teleoperation performed, logged and secured?
- What network, software, fleet-management and manufacturing-system interfaces are supported?
- Who supplies training, preventive maintenance, spare parts and emergency support?
- What are the acceptance criteria for moving from laboratory evaluation to production?
- What happens to production data, learned behaviors and software updates at contract end?
- Which performance claims are measured at a customer site, and which are laboratory or demonstration results?
Bottom line for factory automation teams
Start with Figure 02 when you need the most concrete public production evidence, especially for precise, repetitive sheet-metal handling. Consider Apollo when intralogistics, kit delivery or basic inspection is the bottleneck and you can support a teleoperation-to-autonomy ramp. Evaluate AEON for a BMW-style exploration of mobile, tool-changing work in battery and component manufacturing, but require current pilot results and missing specifications before making a commitment.
For all three, the right next step is a bounded, instrumented pilot with a written safety case and production acceptance criteria. The public record supports serious evaluation—not a claim that humanoid robots are already interchangeable, universally autonomous factory workers.
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