kooktaelee/D2OC
Python and MATLAB codes for Density-Driven Optimal Control (D2OC) using Optimal Transport and Wasserstein distance, enabling decentralized multi-agent / multi-robot non-uniform area coverage.
This project helps manage groups of robots or drones (multi-agent systems) to efficiently cover a specific area, even if some parts need more attention than others. You provide a map indicating which areas need more coverage, and it outputs the flight paths or movement commands for each robot to achieve that non-uniform coverage. This is ideal for operations managers, drone fleet supervisors, or robotics engineers in fields like search & rescue or environmental monitoring.
Use this if you need multiple autonomous agents to collectively cover a physical space, prioritizing certain high-density areas, without central command.
Not ideal if you are controlling a single robot or if your coverage needs are simple and uniform across an entire area.
Stars
12
Forks
1
Language
MATLAB
License
MIT
Category
Last pushed
Mar 03, 2026
Commits (30d)
0
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