Projects Robotics

DecentraliDrones

A decentralised autonomous drone delivery system, trained in simulation with reinforcement learning.

The problem

Delivery drone research usually assumes a central controller. That is convenient and unrealistic: it makes the coordinator a single point of failure and does not scale with fleet size.

What it does

Agents are trained with TD3 inside AirSim on an Unreal Engine environment, and coordinate without a central authority. Navigation, obstacle handling and route decisions are learned in simulation rather than scripted.

The part that mattered

Simulation fidelity. A policy that only works in the simulator it was trained in has learned the simulator, not the task — so environment variation mattered more than reward tuning.

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