Humanoids in Logistics: Where Figure, Apptronik and Agility Actually Ship and Deploy

Current State of Humanoid Deployment in Logistics

The logistics sector has historically prioritized fixed automation, autonomous mobile robots, and structured pick-and-place systems. Humanoid platforms entered this space under the premise that existing warehouse infrastructure, picking algorithms, and material handling workflows could be repurposed without complete facility redesign. This assumption requires rigorous verification against shipped hardware, documented pilot metrics, and manufacturer specifications. The current landscape is defined by early-stage deployments, limited shipping volumes, and a clear hierarchy of validation: shipping hardware first, pilot deployments second, and announcements last.

Three manufacturers dominate current logistics conversations: Figure AI, Apptronik, and Agility Robotics. Each has pursued distinct integration pathways, published different specification baselines, and faced varying operational constraints. This analysis grades their logistics claims strictly by verified hardware delivery, documented pilot outcomes, and manufacturer data. Rendered concepts, stage demonstrations, and forward-looking roadmaps are excluded from primary validation.

Figure AI: From BMW Pilots to Logistics Readiness

Figure AI has primarily validated its Figure 04 platform through manufacturing partnerships, most notably with BMW. While automotive assembly shares logistical overlap with warehouse operations, the two environments differ in floor loading, obstacle density, and task repetition cycles. Figure has shipped Figure 04 units for pilot evaluation, with the company reporting that hardware is being deployed in controlled industrial settings. Manufacturer spec sheets indicate a payload capacity of approximately 20 kg, a focus on dexterous manipulation, and an emphasis on vision-language-action models for task execution.

Logistics-specific claims for Figure remain in the pilot deployment tier. The company has demonstrated bin picking, carton handling, and basic material transport in staged environments. However, published cycle times, uptime percentages, and failure rates for warehouse workflows are not publicly disclosed. The platform relies on external compute for heavy model inference, which introduces latency and network dependency. For logistics operators, the primary constraint is not manipulation capability but throughput consistency and integration with existing warehouse management systems.

Apptronik Apollo: Amazon Pilots and Warehouse Integration

Apptronik has pursued a different validation path, focusing on the Apollo platform for logistics and commercial service environments. Apollo has been deployed in Amazon fulfillment centers as part of a structured pilot program. Manufacturer documentation describes a bipedal design optimized for extended duty cycles, with emphasis on navigation stability, battery management, and safety certification for human-adjacent operations. Apollo's spec sheet highlights a payload capacity near 20 kg, a focus on repetitive material handling, and a modular end-effector system.

Pilot deployment data from Amazon and Apptronik indicates that Apollo is being tested for case transport, shelf replenishment, and pallet staging. The platform's advantage lies in its mechanical simplicity and focus on reliability over complex manipulation. However, warehouse logistics requires precise object interaction, which remains a limitation of Apollo's current gripper configuration. Published metrics show steady integration progress, but cycle speed and pick accuracy remain secondary to navigation and uptime validation. The platform is graded at the pilot deployment tier for logistics, with shipping hardware already in operational testing environments.

Agility Robotics Digit: High-Profile Pilots and Operational Limits

Agility Robotics' Digit platform has received significant attention due to its Amazon pilot program. Digit was designed specifically for logistics, with a focus on carton handling, shelf scanning, and material transport. Manufacturer specifications list a payload capacity of approximately 20 kg, a height optimized for standard shelving, and a design that prioritizes speed and duty cycle over complex dexterity. Agility has shipped Digit units to Amazon for deployment, marking a clear shift from announcement to pilot deployment.

However, operational reality imposes constraints. Digit's gripper mechanism, while functional for standardized cartons, struggles with irregular packaging, flexible materials, and high-precision placement. Published reports indicate that Amazon has adjusted its deployment strategy, focusing on Digit for transport and scanning tasks rather than direct picking. The platform's speed advantages are offset by navigation limitations in dense warehouse layouts and battery replacement requirements. Digit remains a valid pilot deployment for specific logistics subtasks, but its classification as a universal warehouse solution exceeds current hardware capabilities.

Hardware, Specs, and the Shipping Reality

Grading these platforms by hardware delivery reveals a consistent pattern. All three manufacturers have shipped units, but the volumes remain in the pilot and evaluation tier rather than commercial scale. Spec sheets across Figure 04, Apollo, and Digit converge on similar baselines: 20 kg payload, bipedal locomotion, external compute dependency, and modular end-effectors. These specifications reflect engineering compromises between mobility, power consumption, and manipulation complexity.

Warehouse logistics demands metrics that are rarely published transparently. Operators require verified cycle times, mean time between failures, integration APIs for WMS/WCS systems, and total cost of ownership calculations. Current deployments prioritize navigation stability, safety certification, and basic material handling. Complex picking, high-speed sorting, and dynamic task switching remain in the announcement and research phases. Logistics operators should evaluate platforms based on shipped hardware in controlled environments, pilot deployment data from operational partners, and manufacturer spec sheets that detail power consumption, navigation accuracy, and gripper force limits.

India Availability and Landed Cost Estimates

Humanoid logistics platforms are not currently available for direct commercial purchase in India. All three manufacturers operate through pilot programs, partnership evaluations, and controlled deployment agreements. Importing a single unit would require navigating DGFT regulations, BIS certification requirements, and high-duty import structures. Estimated landed costs for a single pilot unit in India, including customs, shipping, and certification, range from INR 2.5 crore to INR 3.5 crore. These figures are clearly flagged as preliminary estimates and do not reflect commercial pricing, which remains undisclosed.

Local availability is limited to research institutions, technology parks, and select logistics firms running government-backed automation pilots. No domestic manufacturing or assembly lines for these platforms exist as of the current reporting period. Indian logistics operators seeking humanoid integration should monitor official manufacturer partnership announcements, BIS certification updates, and DGFT duty classifications for robotics hardware. Until commercial pricing and local support networks are established, pilot deployments will remain the primary access point.

Conclusion: What Logistics Operators Should Actually Watch

Humanoids in logistics are transitioning from concept to early deployment, but the grading hierarchy remains strict. Shipping hardware has occurred, pilot deployments are active but limited in scope, and commercial scale remains an announcement-tier objective. Operators should focus on verified uptime data, WMS integration capabilities, gripper force specifications, and total cost of ownership calculations. Rendered concepts and stage demonstrations do not replace factory video validation, spec sheet verification, and independent pilot reporting.

The logistics sector will adopt humanoid platforms when they demonstrate consistent cycle times, reliable navigation in dense layouts, and clear economic advantage over existing automation. Until then, humanoids will remain specialized tools for material transport, scanning, and repetitive staging tasks. Hardware-first validation, documented pilot metrics, and transparent manufacturer data will determine which platforms transition from evaluation to operational deployment.

References

• Figure AI. (2024). Figure 04 Platform Specifications and Manufacturing Partnership Updates. https://www.figure.ai
• Apptronik. (2023). Apollo Platform Technical Documentation and Amazon Pilot Deployment Updates. https://www.apptronik.com
• Agility Robotics. (2023). Digit Platform Specifications and Amazon Fulfillment Center Pilot Reports. https://www.agilityrobotics.com
• Amazon News. (2023). Agility Robotics Digit Deployment in Fulfillment Centers. https://press.amazon.global
• BMW Group. (2023). Figure AI Figure 04 Pilot Deployment at BMW Manufacturing Facilities. https://www.bmwgroup.com
• DGFT India. (2024). Import Policy and BIS Certification Requirements for Robotics Hardware. https://dgft.gov.in