8wk
Intensive program
80%
Hands-on lab time
12+
Real-world lab exercises
1:6
Instructor-to-trainee ratio
Program philosophy
Built for doing,
not just knowing
Site-to-deployment pipeline
Learn every stage of an AMR project — from facility survey and infrastructure prep through go-live and post-deployment monitoring.
Real hardware, real problems
Work directly on AMR platforms throughout the program. No simulators as a crutch — labs use physical robots in staged facility environments.
ROS 2 & navigation stack
Hands-on configuration of Nav2, SLAM toolbox, costmaps, and fleet management middleware — not just theory.
Industry integration
Connect AMR fleets to WMS and ERP systems. Learn API design patterns, MQTT event buses, and real-time fleet dashboards.
Training time breakdown
Hands-on labs & field work80%
Concepts & theory20%
Technologies covered
ROS 2 (Humble)Nav2SLAM Toolbox
GazeboLiDAR / IMUFleet management
WMS APIsOTA updatesISO 3691-4
RViz 2MQTT / RESTDocker
Week-by-week
The 8-week curriculum
Two phases — each building directly on the last. No week is filler.
Week
1
Phase 1 · Foundations
AMR ecosystem & safety framework
AMR vs AGVISO 3691-4 risk assessmentDrive kinematicsRobot anatomy
TheoryLab intro
Week
2
Phase 1 · Foundations
Sensors, actuators & hardware bring-up
LiDAR / camera calibrationIMU & encoder setupMotor controllersBattery & BMS
Lab
Week
3
Phase 1 · Foundations
ROS 2 configuration & sensor fusion
ROS 2 nodes & topicsEKF state estimationTF2 transformsRViz 2 visualisation
Lab
Week
4
Phase 1 · Foundations
SLAM mapping & localization
SLAM Toolbox (2D)Map creation & storageAMCL localisationMap validation
LabField exercise
Week
5
Phase 2 · Deployment
Nav2 path planning & obstacle avoidance
Global planner (A*)DWB local plannerCostmap tuningRecovery behaviours
Lab
Week
6
Phase 2 · Deployment
Fleet management & traffic coordination
Multi-robot task allocationDeadlock preventionPriority zonesOpen-RMF intro
Lab
Week
7
Phase 2 · Deployment
WMS integration, site prep & commissioning
REST / MQTT APIsWiFi infrastructureFacility zoningAcceptance testing
Field exerciseLab
Week
8
Phase 2 · Deployment
Capstone: full-scale deployment simulation
End-to-end deploymentKPI measurementOTA update rolloutFinal presentation
Capstone
Hands-on labs
12 real-world exercises
Every lab is designed around a specific deployment scenario. You'll debug real failures, tune live navigation stacks, and ship configs to actual robots.
Lab 01
Robot hardware bring-up & sensor validation
Physically assemble and boot an AMR platform. Validate all sensor feeds using RViz2 before the robot takes a single step.
First motion — robot drives a predefined route with no errors
Lab 02
LiDAR calibration & point-cloud quality
Intrinsic and extrinsic calibration of a 2D LiDAR. Diagnose and fix common noise and dropout patterns.
Clean scan profile matching reference ground-truth map
Lab 03
EKF odometry fusion
Configure robot_localization with wheel odometry + IMU. Measure drift over a 50m run before and after tuning.
Localisation error <5cm over 50m closed loop
Lab 04
SLAM mapping of a mock warehouse floor
Drive a physical AMR through a staged 20×15m facility. Generate, validate, and store an operational map with SLAM Toolbox.
Map accepted by site survey checklist — ready for Nav2
Lab 05
Nav2 stack configuration & goal navigation
Configure the full Nav2 bringup with costmaps, planner, and controller. Send goals via CLI and action server.
Robot navigates 10-point mission without manual intervention
Lab 06
Costmap tuning for narrow aisles
Reproduce a common deployment failure — robot refuses to enter a 900mm aisle. Tune inflation and footprint parameters to resolve it.
Aisle navigation success rate improved from 0% to >95%
Lab 07
Dynamic obstacle avoidance stress test
Introduce moving people and forklift proxies. Measure stop, re-route, and recovery response times under load.
Zero collision events across 30-minute stress run
Lab 08
Multi-robot fleet — traffic deadlock scenario
Deploy 3 robots on a shared lane network. Intentionally trigger a deadlock, diagnose it, then fix with priority rules.
Fleet throughput restored — zero deadlocks in 1-hour run
Lab 09
WMS task dispatch via REST API
Build a simple dispatcher that pushes pick-and-place tasks from a mock WMS to the AMR fleet via HTTP REST calls.
End-to-end task cycle <3s from WMS trigger to robot motion
Lab 10
Facility site survey & WiFi coverage audit
Use a standardised site checklist to survey a facility. Identify dead zones, floor irregularities, and reflector placement requirements.
Completed site readiness report — approved for robot commissioning
Lab 11
Acceptance testing & KPI benchmarking
Run a full acceptance test suite against a defined SLA. Measure mission success rate, cycle time, MTBF, and localisation accuracy.
Signed-off test report — all KPIs meet deployment SLA
Lab 12
OTA firmware update & rollback drill
Push a staged firmware update to a 3-robot fleet. Simulate a bad update — execute emergency rollback with zero downtime.
Successful rollback in under 90 seconds across all 3 units
Eligibility
Who this program is built for
🎓
Fresh graduates
Mechanical, electrical, or CS engineering graduates who want to specialise in robotics deployment without a multi-year learning curve.
Prerequisites
Basic Linux command line
Python or C++ fundamentals
Undergraduate engineering degree
⚙️
Industry engineers
Automation, controls, or mechatronics engineers transitioning into AMR-focused roles within warehousing, manufacturing, or logistics.
Prerequisites
1+ year industry experience
Familiarity with embedded systems
Basic networking concepts
🏢
Company cohorts
Companies deploying or planning to deploy AMR fleets can enrol teams for dedicated cohort training — customised to your robot platform.
Corporate track includes
Platform-specific lab customisation
On-site delivery option
Post-training support package
After graduation
What you'll be able to do
✓
Configure and tune a full ROS 2 / Nav2 navigation stack from scratch
✓
Create validated SLAM maps for real facilities and manage map lifecycles
✓
Conduct facility site surveys and produce deployment readiness reports
✓
Design and execute multi-robot fleet coordination with deadlock prevention
✓
Integrate AMR fleets with WMS/ERP systems using REST and MQTT
✓
Write and execute structured acceptance test plans against defined SLAs
✓
Apply ISO 3691-4 safety standards in a real-world risk assessment
✓
Manage OTA firmware rollouts and execute emergency rollback procedures
Certification of Completion
Certified AMR Deployment Engineer
Graduates who complete all labs and the capstone project receive a verifiable digital credential recognised by AMR integrators and logistics technology companies across the industry.
Verifiable digital badge (Credly)
Capstone project portfolio entry
Access to alumni deployment network
LinkedIn credential integration
Recognised by 40+ AMR integrator companies
Next cohort
Ready to deploy
real robots?
Cohort 4 begins August 11, 2025. Seats are capped at 18 to maintain the 1:6 instructor ratio. Applications close July 25.
Aug 11
Start date
18
Seats available
8 wk
Full-time, in-person