Autonomous Mobile Robots (AMRs) and Automated Guided Vehicles (AGVs) both automate warehouse material movement — but with fundamentally different architectures, operational profiles, and total cost of ownership that make each optimal for different deployment scenarios. Choosing the wrong technology is expensive: a full AGV system commitment in an environment that changes frequently leads to months of re-engineering; deploying AMRs where maximum throughput is needed leads to congestion and throughput shortfalls. This guide provides the decision framework that warehouse operations and logistics technology leaders need.
The Fundamental Difference
AMR vs AGV: Navigation Architecture
AGVs (Automated Guided Vehicles) follow fixed physical guidance — magnetic tape, wire, reflective markers, or QR codes embedded in the floor. They know exactly where they are because the path is physically defined. AMRs (Autonomous Mobile Robots) build a map of the environment using SLAM (lidar, camera, or depth sensors) and navigate dynamically — computing optimal paths in real time, avoiding obstacles, and adapting to layout changes. This architectural difference drives everything: AGVs have higher predictability and throughput on fixed routes; AMRs have higher flexibility but more complex deployment and performance characterisation.
AGV vs AMR Comparison Matrix
| Dimension | AGV | AMR |
|---|---|---|
| Navigation | Fixed infrastructure (tape/wire/QR) | SLAM — autonomous map-based navigation |
| Layout flexibility | Low — infrastructure change required for route change | High — update map, redeploy software |
| Throughput predictability | Very high — deterministic fixed-route timing | Medium — dynamic routing adds variability |
| Obstacle handling | Stop and wait — cannot navigate around obstacles | Dynamic rerouting — finds alternative path |
| Installation complexity | High — floor infrastructure required | Low — deploy and train map in 1–2 days |
| Max payload | 10,000kg+ (heavy load AGVs) | Typically 100–2,000kg (AMR market) |
| Upfront cost | Higher — infrastructure + vehicle | Lower — vehicle only |
| Best environment | Predictable, structured, high-volume fixed routes | Dynamic, mixed-traffic, flexible operations |
AMR market
AMR market growing 25% annually in 2026, overtaking AGV new deployments by volume — the flexibility advantage and lower installation barrier make AMRs the default choice for most new warehouse automation projects
10,000kg
Maximum payload of heavy-load AGV systems — used in automotive manufacturing and steel processing where AMRs cannot match the structural payload requirements. AGV remains dominant in heavy-industry applications
MiR, Locus, 6RS
The leading AMR vendors in warehouse and distribution: MiR (now Teradyne) for autonomous transport AMRs, Locus Robotics for goods-to-person picking, 6 River Systems (Shopify) for collaborative picking workflows
Choose AGV For
High-throughput fixed routes where predictability is paramount: automotive assembly line part delivery (same route, 10,000 cycles/day), cold storage material movement (people-free zones where AMR mapping is harder), very heavy loads above AMR payload limits, and environments with extremely clean floors and simple layouts where the infrastructure cost is justified by throughput requirements. If your operation never changes layout and runs at maximum throughput, AGV's determinism is an asset.
Choose AMR For
Ecommerce fulfilment with SKU proliferation and changing slotting, mixed-use facilities where both humans and robots share space, multi-shift operations with flexible task assignment, any facility expecting layout changes within 2–3 years, and new deployments where floor infrastructure cost is prohibitive. AMR's rapid deployment (1–2 days vs 2–4 weeks for AGV infrastructure) and reconfigurability make it the lower-risk investment for most modern warehouses.
Collaborative Picking (AMR Model)
The most deployed AMR use case: goods-to-person picking where AMRs carry mobile shelving units (pods) from storage to stationary pickers, eliminating picker walking. Kiva-model (Amazon Robotics, Geek+, Quicktron). Or person-to-goods collaboration where AMRs follow pickers through the warehouse carrying the tote, eliminating cart pushing. 6 River Systems Chuck and Locus Robotics follow the picker and handle tote transport. Either model reduces picker walking by 60–80%, the primary labour efficiency gain.
Fleet Sizing Calculation
AMR fleet sizing: (Moves/hour required × average travel time per move in minutes) ÷ 60 × utilisation factor (0.7–0.8) = AMRs needed. Example: 200 moves/hour × 3 min average travel / 60 × 0.75 = 13.3 AMRs → round up to 15 with 2 spares. Add charging infrastructure: 1 charger per 3–4 AMRs for continuous operation. Engage the AMR vendor's professional services team for detailed simulation using your facility map and historical order data before purchase commitment. ROI payback: typically 18–30 months for warehouse AMR deployments at current hardware costs.
Warehouse Robot Selection and Implementation
Our software development, ML development, and IoT solutions teams advise on warehouse robot selection and integrate AMR/AGV systems with WMS and ERP platforms. Book a free advisory session.