The ZeeBot rack-climbing warehouse robot integrates horizontal movement and vertical climbing into a single autonomous device. It travels on the warehouse floor, grips onto vertical rack structures, and ascends to retrieve or store totes at heights up to 14 meters—eliminating the need for separate stacker cranes, conveyors, or lift mechanisms.
A rack-climbing warehouse robot is an autonomous mobile robot (AMR) built for automated storage and retrieval (AS/RS). Unlike floor-bound AMRs, it physically ascends vertical rack structures up to 14 meters, combining the functions of a shuttle, stacker crane, and transport AMR into one device.
The robot receives a command from the WMS and navigates to the target rack via LiDAR SLAM. It engages servo-driven grippers that lock onto vertical rack rails and pull the robot upward. IMU sensors maintain stable orientation during ascent. At the target level, it halts with ±2mm accuracy and extends its extraction mechanism to retrieve or insert a tote, then descends and delivers—all in one continuous operation.
Traditional AS/RS separates horizontal transport from vertical access, requiring conveyor handoffs between devices. The rack-climbing robot eliminates this by combining floor travel and climbing in one continuous operation—removing bottlenecks, reducing equipment count, and simplifying warehouse control architecture.
Performs floor travel and vertical climbing in one continuous motion without any load transfers between devices. The dual-mode drive system switches between wheeled navigation and rack-mounted climbing, eliminating handoff delays and reducing warehouse equipment footprint.
Climbs to 5-tier rack positions (up to 14 meters) in approximately 10 seconds while maintaining ±2mm positioning accuracy at any height. The servo-controlled climbing mechanism uses dual-gripper engagement for redundant grip points, with dynamic force adjustment ensuring stable ascent and descent under full 30 kg load. The onboard IMU continuously corrects drift during vertical travel.
A cloud-based AI platform coordinates 100+ robots across sites up to 500,000 m². The fleet management system dynamically assigns tasks based on order priorities, optimizes travel paths, and balances workload for maximum throughput.
LiDAR SLAM provides real-time floor localization, 3D vision detects tote positions and rack alignment, and IMU compensates for motion during climbing. This multi-sensor fusion ensures consistent ±2mm positioning accuracy on both horizontal and vertical planes.
Retrieves totes from front, rear, left, right. This bidirectional access lets the robot service both sides of an aisle without repositioning, doubling picking density per aisle and enabling ultra-narrow aisle configurations.
Natively supports VDA 5050 for integration with third-party fleet management and mixed-vendor environments. Also supports MQTT and REST API for direct WMS connectivity, ensuring interoperability with existing AGVs, AMRs, and warehouse control systems.
360° LiDAR provides continuous floor collision avoidance, while redundant fall-prevention sensors engage during climbing. Dynamic grip force control adjusts clamping pressure based on position feedback, and an instant emergency stop halts all motion upon anomaly detection.
Operates on standard shelving without proprietary rail systems. Capacity scales by adding robot units rather than building new conveyors. Start with a small fleet and expand during peak seasons—converting automation from fixed capital expense to flexible operating cost.
ZeeBot operational specifications measured under standard warehouse conditions (20°C, level floor, standard racking). Throughput varies by tote weight, rack config, and fleet size.
Handle high-SKU, high-velocity order fulfillment with goods-to-person picking workflows. The rack-climbing robot retrieves totes from any rack position within seconds, enabling rapid order assembly for same-day and next-day delivery requirements. The AI fleet orchestrator dynamically prioritizes urgent orders across the robot fleet.
Support high-volume parcel sorting and consolidation operations with scalable automation. The modular robot fleet can be rapidly expanded during seasonal peaks (such as Singles' Day, Black Friday) by deploying additional robot units without installing new conveyor lines or modifying rack infrastructure.
Maximize storage density in space-constrained urban locations where real estate costs are highest. The rack-climbing robot accesses rack heights up to 14 meters in ultra-narrow aisles, achieving 48 totes/m² storage density. This enables dark stores to hold more SKUs in smaller footprints while maintaining fast retrieval for last-mile delivery networks.
Serve multiple clients with varying SKU profiles and throughput requirements from a single automated facility. The rack-climbing robot's flexible tote compatibility and software-configurable storage zones allow rapid reconfiguration between clients, while the VDA 5050 protocol enables integration with diverse client WMS systems.
Manage high-value inventory with precision tote handling and full traceability. The ±2mm positioning accuracy ensures correct item retrieval in complex multi-SKU environments, reducing picking errors. WMS integration provides real-time inventory tracking with barcode/RFID verification at each storage and retrieval operation.
Operate in temperature-controlled environments (0°C to 40°C) for pharmaceutical and cold chain warehousing. The LiFePO4 battery system with intelligent thermal management ensures reliable performance across temperature ranges. WMS integration maintains strict batch traceability and FIFO/FEFO compliance required by pharmaceutical regulatory standards and cold chain documentation requirements.
An AMR combining floor travel with vertical climbing up to 14m for tote retrieval/storage.
Standard steel racks (5+ tiers), various tote sizes. 4-way extraction in ultra-narrow aisles.
REST API, OPC UA, MQTT, VDA 5050. SAP EWM, Manhattan, Blue Yonder compatible. 2–4 week integration.
6–8 weeks survey to go-live. Uses existing shelving; capacity scales by adding units.
Redundant fall-prevention sensors, servo grip control, 360° LiDAR, instant emergency stop, auto-recovery.
LiFePO4: 8+ hours, 80% in ~1.5 hours via auto-docking. BMS thermal safety at 0°C–40°C.
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