HamptonianCoDrone Academy
Engineering and automation · Mission 10

Autonomy Lab

Write it once. Fly it every time. · Operation LOOPBACK · 5 days suggested (1–7)

A robotics lab is building an automated drone cell. Your crew writes the flight logic. Engineers automate drone tasks — inspections, deliveries, light shows — by writing programs that are tested in simulation first, then on hardware. Good automation is predictable, debuggable and safe.

Learning targets
  • ◆ I can use sequences, loops and sensor conditions to automate a flight.
  • ◆ I can debug a program by comparing expected and actual behavior.
  • ◆ I can explain why engineers test in simulation before hardware.
Skills & CoDrone topics
CodingProblem solvingPerseveranceMission planningBlockly programmingPython programmingSensors and obstacle detectionFlight pathsTroubleshooting
Crew roles
  • Pilot: Runs the program and stands ready to take over.
  • Mission Commander: Owns the code and the test plan.
  • Engineer / Safety Observer: Reviews code for safety and records test results.

Simulator challenges

FlightCraft
Calibration Hover

Before any automation: confirm the drone holds a stable hover, then land on the test pad.

Fly it →
SH8 m × 8 m · grid 1 m · dashed = overhead
DroneDash
Test Cell Gates

Fly the calibration gates in order, then land on the test pad. Your best run becomes the ghost for your crew.

Fly it →
SH123458 m × 8 m · grid 1 m · dashed = overhead
CodePilot
Automated Inspection Cell

Automate a full cycle: approach the test board using the front sensor, hold for inspection, return, and inspect the two side stations with a loop.

Fly it →
Board faceStation LStation RH8 m × 8 m · grid 1 m · dashed = overhead
CodePilot
Debug the Square

This program is supposed to fly a square and land at home — but it has a bug. Run it, watch where it goes wrong, and fix it.

Fly it →
Corner 1Corner 2Corner 3H8 m × 8 m · grid 1 m · dashed = overhead
Classroom flight · 45 min
Simulation vs. Reality

Fly your Automated Inspection Cell on a real drone and measure how reality differs from the simulation.

  • ☐ Recorded predictions before running
  • ☐ Measured three results
  • ☐ Changed one variable and re-tested
  • ☐ Completed the safety review
  • ☐ Program uses a sensor and a loop or sequence correctly
Classroom flight · 35 min
Blockly to Python

Build the Debug the Square fix in Robolink Blockly, then compare it with the Python version this app exports.

  • ☐ Built the corrected program in Blockly
  • ☐ Matched blocks to Python lines
  • ☐ Safe hardware run
Simulated vs. real

Motion-capture tracking (simulated): The simulation shows the drone's exact path so you can compare it with the plan. Real CoDrone EDU: CoDrone EDU estimates position with its optical flow sensor; get_pos_x()/get_pos_y() report it. In class, crews mark the floor and measure.

Mission conclusion
Cell certified for automation.

You wrote, simulated, debugged and hardware-tested an automated flight — the exact loop real robotics engineers follow. Simulation first, hardware second, safety always.

Careers: Robotics engineer · Automation technician · Software test engineer