Introduction
Mobile robots are no longer “nice to have”. With labor constraints, higher logistics costs, and faster changeovers, manufacturers and warehouses increasingly rely on automated material transport. The decision usually comes down to AGV (Automated Guided Vehicle), AMR (Autonomous Mobile Robot), or a hybrid fleet.
This guide explains the differences in practical, engineering terms, and includes real deployment references from Motionwell projects.
What is an AGV?
An Automated Guided Vehicle (AGV) follows predefined routes using guidance infrastructure. It is typically chosen when routes are stable, traffic rules are clear, and deterministic operation matters.
| Guidance method | Typical signal | Facility impact | Best fit scenarios |
|---|---|---|---|
| Magnetic tape | Magnetic track on floor | Requires floor work during install and changes | Stable routes, fast commissioning, controlled aisles |
| Painted/optical line | Visual line tracking | Needs line maintenance and clean floor | Simple paths, low traffic environments |
| Wire guidance | Embedded wire with electromagnetic field | Higher install complexity | Long-term fixed layouts, robust path enforcement |
| QR / markers | Fixed markers at points | Requires marker placement and upkeep | Defined checkpoints, repeatable docking points |
What is an AMR?
An Autonomous Mobile Robot (AMR) navigates dynamically using onboard sensors and software. It is typically chosen when layouts change, obstacles are common, or fast scaling matters.
| Navigation stack element | What it does | Practical benefit |
|---|---|---|
| SLAM | Localization and mapping | Works in changing layouts with software updates |
| LiDAR | Distance sensing and scan matching | Reliable navigation and obstacle detection |
| Cameras | Visual understanding and docking support | Better perception for mixed environments |
| Path planning and avoidance | Dynamic route generation | Less manual traffic engineering, better flexibility |
Key Differences: AGV vs AMR
| Factor | AGV | AMR |
|---|---|---|
| Navigation | Fixed routes | Dynamic routes |
| Layout changes | Physical rework | Mostly software changes |
| Predictability | Very deterministic on fixed lanes | High, but depends on traffic policy and mapping |
| Deployment speed | Medium (infrastructure work) | Faster (mapping + software) |
| Best environments | Stable, high-volume flows | Dynamic, mixed-traffic operations |
| Integration focus | Fleet control + traffic rules | Fleet control + localization + safety policy |
Selection Matrix: Choose AGV, AMR, or Hybrid
| Requirement / constraint | Better fit | Notes from an integrator’s perspective |
|---|---|---|
| Routes rarely change and aisles are fixed | AGV | Guidance infrastructure becomes part of your “plant standard” |
| Frequent layout changes and seasonal SKU mix | AMR | Reduce physical rework; focus on software governance and mapping |
| High pedestrian / forklift interaction | AMR or Hybrid | Requires clear safety zoning and traffic policy either way |
| Heavy loads on a repetitive loop | AGV or Hybrid | Determinism and high duty cycles can favor guided routes |
| Need mobile manipulation (pick/place at stations) | AMR + Cobot (Hybrid) | Docking + perception + manipulation becomes the key engineering challenge |
| Minimal facility modification allowed | AMR | Typical ramp-up is faster when you avoid floor work |
| Strict traceability and data handoff | Both | Architecture matters more than robot type (interfaces, IDs, state machine) |
Real-World References From Motionwell
The “right” choice is easier when you anchor it to real production constraints. Below are two Motionwell references that illustrate different intralogistics patterns.
Reference 1: Project P23078 — QA Lab Automation (Singapore)
This program demonstrates AMR + Cobot integration for high-mix, high-traceability workflows.
| Aspect | Delivered implementation (high-level) |
|---|---|
| Business goal | Automate sample logistics and material testing in a high-throughput QA lab |
| Mobile platform | MiR AMR class platform with task dispatch and autonomous navigation |
| Manipulation | Universal Robots collaborative arm for tray pick/place with vision support |
| Storage model | 70 positions rack (7 rows × 10 columns) managed as inventory states |
| Test cell integration | PLC orchestrates multiple Instron test cells and sample state transitions |
| Data handling | Test files are auto-named and uploaded to a server for traceability |
Reference 2: Project 0020 — ASRS Warehouse Automation (Medical Consumables)
This program demonstrates a stable, high-volume warehouse pattern where deterministic flows and WMS traceability are critical.
| Aspect | Delivered implementation (high-level) |
|---|---|
| Industry | Medical consumables warehouse (BD syringe cartons) |
| Core automation | ASRS stacker crane + pallet conveyor lines for in/outbound |
| Robotics | FANUC palletizing robot integrated with conveyor and safety fencing |
| Systems | WMS for location management and inventory traceability |
| Why it matters | When flows are fixed and throughput is high, deterministic logistics can outweigh maximum flexibility |
Cost and Engineering Considerations
Rather than comparing “AGV price vs AMR price”, compare the full engineering footprint: infrastructure, change management, commissioning, and lifetime support.
| Cost driver | AGV pattern | AMR pattern |
|---|---|---|
| Infrastructure | Higher (routes, markers, stations) | Lower (mapping + docking points) |
| Layout changes | Physical change orders | Mostly software + validation |
| Maintenance profile | Simpler sensors, more floor upkeep | More sensors/software, less floor upkeep |
| Commissioning | Infrastructure + traffic rules | Mapping + traffic rules + perception tuning |
| Integration effort | Similar for both | Similar for both |
| Engineering checklist item | Why it matters |
|---|---|
| Define payload, cycle time, and station dwell | Determines fleet sizing and queue strategy |
| Clarify docking tolerance at each station | Drives mechanical design, sensors, and recovery logic |
| Decide your traceability model (IDs, states, audit trail) | Prevents “robot works but data is wrong” failures |
| Choose safety strategy early (zones, speed, E-stops, recovery) | Avoids late redesign and commissioning delays |
Frequently Asked Questions
| Question | Answer |
|---|---|
| How do I estimate how many robots I need? | Start from takt time and transport demand: trips per hour, average travel distance, station dwell time, and peak-hour variability. A good sizing model includes buffering time and “traffic friction” in shared aisles. |
| Do AGVs always require magnetic tape? | No. Magnetic tape is common, but AGVs can also use wires, QR/markers, or other guidance infrastructure. The key is whether you are willing to treat routes as fixed assets that change through controlled engineering updates. |
| Can AMRs run in regulated environments (e.g., labs or cleanrooms)? | Yes, with the right materials, cleaning processes, and validation approach. In regulated workflows, the integration architecture and data traceability often matter more than the navigation method. |
| What systems do you typically integrate with? | WMS/MES/LIMS integration depends on the workflow. We usually define a clear interface for work orders, status feedback, and result data (IDs, timestamps, and error codes), then validate end-to-end traceability. |
Conclusion
There is no universal winner between AGV and AMR. The right choice depends on your facility stability, traffic complexity, traceability requirements, and how often you change the layout.
Motionwell is an authorized partner for both SIASUN AGV and MiR AMR platforms, and we design the integration architecture around your workflow and validation needs.
Explore our dedicated solution pages for more details:
| Solution | Best for |
|---|---|
| AMR Solutions | Dynamic environments, flexible routing, mobile manipulation |
| AGV Solutions | Stable routes, high-volume flows, deterministic logistics |
Ready to explore mobile robot solutions? Contact us at /contact/ for a consultation and site assessment.