M
Mobility
Move people, robots and services through the city.
Robotics · Autonomy · Sustainable cities
Engineering Citiesfor a Sustainable Future
Build, programme and simulate autonomous robots while exploring how mobility, networks and optimisation shape more sustainable cities.
ManoCity for SchoolsThe MANO framework
MANO is how the city works.
Four engineering ideas sit at the centre of ManoCity.
A
Autonomy
Sense, decide and act without a memorised route.
N
Networks
Connect vehicles, infrastructure and data.
O
Optimisation
Balance time, energy, distance and resources.
MMobility+AAutonomy+NNetworks+OOptimisation
Sustainability outcome
MANO decisions are measured by their impact.
Sustainability is the outcome: students compare what the city used, how long it took and the estimated environmental cost.
Journey time
Time
How long did the mission take?
Energy use
Wh
How much energy did the route require?
Estimated emissions
CO₂e
What was the modelled environmental impact?
System efficiency
Efficiency
Could the same task be completed with less?
The learning loop
From code to city.
Every ManoCity activity follows the same engineering process: understand the problem, build a solution, test it and improve it with evidence.
Learn
Build the programming and engineering foundations.
Simulate
Test autonomous behaviour in a digital city.
Build
Move the same ideas into ManoBot and physical models.
Measure
Compare time, energy, distance and estimated emissions.
Improve
Refine the system and test a better decision.
Learn → Simulate → Build → Measure → Improve
The city is the classroom
See how one decision changes the system.
A route is never just a line on a map. It affects travel time, energy demand, passenger movement, road use and environmental impact.
Programme
Write clear logic with Python or Blockly.
Observe
Watch the robot respond to roads, signals and missions.
Compare
Use measured results instead of guessing.
Explain
Connect the code to a real engineering outcome.
One connected platform
One ManoCity. Three environments.
Start in software, shape the city in 3D, then carry the same engineering ideas into a physical ManoBot challenge.
Simulator
Write MicroPython, navigate roads, collect passengers and compare mission performance in the ManoCity digital twin.
Open Simulator →
3D Labs
Design buildings, roads and infrastructure, then save the city you want to use in the simulator.
Build in 3D →
Physical ManoCity
Transfer code and engineering ideas to a real ManoBot, physical city map and classroom challenge.
See the Physical City →Sustainability
Every decision has an impact.
The fastest route is not always the most sustainable. ManoCity helps learners balance time, energy, emissions and the needs of the wider system.
Route A
- Time
- 8.4 min
- Energy
- 74 Wh
- CO₂
- 62 g CO₂
Route B
Lower impact- Time
- 7.9 min
- Energy
- 58 Wh
- CO₂
- 48 g CO₂
Built to grow
One platform. Different depths.
The same city can introduce programming at school, support systems engineering at university and provide a base for advanced mobility research.
Schools
Build strong foundations
Learn Python, sensors, navigation and sustainable design through structured missions.
Universities
Engineer complete systems
Connect robotics, embedded systems, autonomy, intelligent transport and data.
Research
Extend the city
Explore digital twins, V2X, optimisation and cooperative urban mobility.
For schools
Bring ManoCity into the classroom.
One platform for coding, robotics, autonomous systems and sustainable-city engineering.
- Ready-made learning missions
- Physical + digital activities
- School challenges and competitions